senior software engineer analytics

VERSA Integrated Solutions

<p>Position: AI/ML Engineer</p><p>Location: Washington, DC Metro Area (Hybrid/Onsite based on customer requirements)</p><p>Employment Type: Full-Time</p><p>Salary: Commensurate with Experience</p><p>About VERSA Integrated Solutions</p><p>VERSA Integrated Solutions is a premier provider of Information Technology, Artificial Intelligence, Cybersecurity, Cloud, Data Analytics, and Engineering services supporting Federal Government agencies. We help agencies modernize operations through innovative technologies, secure architectures, and mission-driven solutions. Our teams work on high-impact initiatives that improve decision-making, operational efficiency, and citizen services.</p><p>Position Summary</p><p>VERSA Integrated Solutions is seeking an experienced AI/ML Engineer to design, develop, deploy, and maintain Artificial Intelligence (AI) and Machine Learning (ML) solutions supporting Federal Government customers. The successful candidate will work closely with data scientists, software engineers, cloud architects, cybersecurity professionals, and business stakeholders to build intelligent applications that leverage predictive analytics, machine learning, generative AI, and large language models (LLMs).</p><p>The AI/ML Engineer will support the full lifecycle of AI solutions&mdash;from data preparation and model development to deployment, monitoring, optimization, and governance&mdash;while ensuring compliance with federal security, privacy, and Responsible AI requirements.</p><p>Position Objectives</p><p>The AI/ML Engineer will:</p><ul><li>Design and implement scalable AI and ML solutions.&bull; Build and optimize machine learning models for structured and unstructured data.&bull; Develop data pipelines to support AI workloads.&bull; Integrate AI capabilities into enterprise applications.&bull; Ensure AI solutions comply with federal security, privacy, and governance requirements.&bull; Collaborate with cross-functional teams to deliver mission-focused outcomes.</li></ul><p>Major Duties &amp; Responsibilities</p><p>AI &amp; Machine Learning Development</p><ul><li>Design, develop, train, test, and deploy machine learning models.&bull; Build supervised, unsupervised, reinforcement learning, and deep learning solutions.&bull; Develop predictive analytics and classification models.&bull; Optimize model performance and accuracy through feature engineering and hyperparameter tuning.&bull; Build reusable AI components and services.</li></ul><p>Generative AI &amp; Large Language Models</p><ul><li>Develop solutions using Large Language Models (LLMs).&bull; Implement Retrieval-Augmented Generation (RAG) architectures.&bull; Engineer prompts and fine-tune models where appropriate.&bull; Evaluate AI model outputs for accuracy, explainability, and bias.&bull; Support secure deployment of generative AI capabilities.</li></ul><p>Data Engineering &amp; Preparation</p><ul><li>Build and maintain data ingestion and transformation pipelines.&bull; Clean, normalize, and prepare structured and unstructured datasets.&bull; Collaborate with Data Engineers to optimize data availability and quality.&bull; Implement feature stores and model-ready datasets.</li></ul><p>MLOps &amp; Model Lifecycle Management</p><ul><li>Automate model training, testing, deployment, and monitoring.&bull; Develop CI/CD pipelines for machine learning solutions.&bull; Monitor model drift, performance degradation, and retraining needs.&bull; Maintain version control for models, datasets, and code.</li></ul><p>Responsible AI &amp; Governance</p><ul><li>Implement Responsible AI principles including fairness, transparency, explainability, and accountability.&bull; Ensure compliance with NIST AI Risk Management Framework, Executive Orders, and agency-specific AI policies.&bull; Document AI models, assumptions, limitations, and validation results.</li></ul><p>Collaboration &amp; Innovation</p><ul><li>Partner with software developers, cloud engineers, and business analysts to integrate AI into enterprise solutions.&bull; Present technical findings and recommendations to stakeholders.&bull; Evaluate emerging AI technologies and recommend improvements.</li></ul><p>Required Technical Skills</p><ul><li>Python&bull; SQL&bull; TensorFlow&bull; PyTorch&bull; Scikit-learn&bull; Pandas&bull; NumPy&bull; Hugging Face Transformers&bull; LangChain or similar orchestration frameworks&bull; Azure AI Services or Azure Machine Learning&bull; AWS SageMaker (preferred)&bull; Git/GitHub&bull; Docker&bull; Kubernetes&bull; RESTful APIs</li></ul><p>Preferred Skills</p><ul><li>Experience with Retrieval-Augmented Generation (RAG)&bull; Prompt engineering for LLMs&bull; Vector databases (e.g., Pinecone, Azure AI Search)&bull; Knowledge graph integration&bull; Natural Language Processing (NLP)&bull; Computer Vision&bull; Time-series forecasting&bull; Knowledge of FedRAMP and Zero Trust environments</li></ul><p>Required Qualifications</p><ul><li>Strong analytical and problem-solving skills.&bull; Excellent written and verbal communication skills.&bull; Ability to translate business requirements into AI-driven technical solutions.&bull; Experience working in Agile/DevSecOps environments.&bull; Experience supporting federal government customers is highly desirable.</li></ul><p>Education</p><p>Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics, Statistics, or a related field. A Master's degree is preferred. Equivalent experience may be substituted for education.</p><p>Experience Levels</p><p>Junior (0&ndash;4 Years)</p><ul><li>Experience with Python and machine learning fundamentals.&bull; Exposure to cloud platforms and data science tools.&bull; Participation in AI/ML projects through coursework, internships, or professional experience.</li></ul><p>Intermediate (5&ndash;9 Years)</p><ul><li>Development and deployment of production AI/ML models.&bull; Experience with MLOps pipelines and cloud AI services.&bull; Collaboration with cross-functional software development teams.</li></ul><p>Senior (10&ndash;14 Years)</p><ul><li>Leadership in designing enterprise AI solutions.&bull; Expertise in generative AI, LLMs, and Responsible AI practices.&bull; Experience mentoring junior engineers and leading technical initiatives.</li></ul><p>Subject Matter Expert (15+ Years)</p><ul><li>Recognized authority in enterprise AI strategy and implementation.&bull; Experience shaping AI governance and modernization initiatives for large organizations.&bull; Trusted advisor to executive leadership on AI adoption and emerging technologies.</li></ul><p>Preferred Certifications</p><ul><li>Microsoft Certified: Azure AI Engineer Associate&bull; Microsoft Certified: Azure Data Scientist Associate&bull; AWS Certified Machine Learning &ndash; Specialty&bull; Google Professional Machine Learning Engineer&bull; TensorFlow Developer Certificate&bull; Databricks Certified Machine Learning Professional&bull; ITIL&reg; 4 Foundation (preferred)</li></ul><p>Desired Federal Experience</p><p>Experience supporting one or more of the following agencies is highly desirable:</p><ul><li>U.S. Census Bureau&bull; National Institutes of Health (NIH)&bull; Centers for Medicare &amp; Medicaid Services (CMS)&bull; Department of Commerce&bull; Department of Homeland Security (DHS)&bull; Department of Defense (DoD)&bull; Department of Labor (DOL)</li></ul><p>Security Clearance</p><ul><li>Ability to obtain and maintain a Public Trust or higherclearance, depending on customer requirements.</li></ul><p>Work Environment</p><ul><li>Hybrid or onsite within the Washington, DC Metro Area based on customer requirements.&bull; Collaborative, fast-paced environment supporting mission-critical federal AI initiatives.&bull; Occasional travel to customer sites may be required.</li></ul><p>Why Join VERSA?</p><p>At VERSA, you'll work alongside experts delivering innovative AI solutions that help federal agencies solve complex mission challenges. We invest in continuous learning, professional certifications, and opportunities to work with cutting-edge technologies, including machine learning, generative AI, cloud platforms, and advanced analytics.</p><p>Equal Employment Opportunity</p><p>VERSA Integrated Solutions is an Equal Opportunity Employer. We are committed to creating an inclusive workplace where all employees are respected, valued, and empowered to succeed. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable law.</p><p>Pay: $118,467.98 - $142,671.13 per year</p><p>Benefits:</p><ul><li>401(k)</li><li>401(k) matching</li><li>Dental insurance</li><li>Health insurance</li><li>Paid time off</li><li>Retirement plan</li></ul><p>Work Location: Hybrid remote in Washington, DC 20591</p>

Software Engineer - Data, AI/ML & Analytics

easyJet

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  Luton/Hybrid
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 When it comes to innovation and achievement there are few organisations with a better track record. Join us and you&rsquo;ll be able to play a big part in the success of our highly successful, fast-paced business that opens up Europe so people can exercise their get-up-and-go. With almost 300 aircraft flying over 1,000 routes to more than 32 countries, we&rsquo;re the UK&rsquo;s largest airline, the fourth largest in Europe and the tenth largest in the world. Set to fly more than 90 million passengers this year, we employ over 10,000 people. It&rsquo;s big-scale stuff and we&rsquo;re still growing.
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  Job Purpose
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 The Senior Analytics Engineer leads the development and optimisation of our advanced analytics ecosystem, ensuring that data is not only fit for purpose but also robustly designed for scalability, reusability, and actionable insights. This role bridges technical expertise and strategic vision to deliver enterprise-grade data solutions, supporting high-impact business use cases across multiple domains
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  Job Accountabilities
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 To shape and manage future direction of easyJet&rsquo;s Data Engineering practice, focused on defining, designing and deploying critical analytical pipelines supporting high-quality and reuseable data assets:
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   Define and drive the future direction of data engineering and analytics practices, ensuring alignment with business goals and technological advancements.
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   Design and implement sophisticated data pipelines and transformations, delivering curated, high-quality datasets for advanced analytics, reporting, and AI/ML applications.
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   Act as a technical leader and mentor to Analytics Engineers, BI Analysts, and Data Scientists, ensuring cohesive methodologies and enhancing organisational data literacy across the business domains.
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   Serve as a senior technical Data Steward, championing best practices in data governance, discoverability, and usage, while ensuring end-to-end documentation and observability of analytical pipelines.
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   Leads collaboration with BI Analysts and Data Scientists to refine methodologies, enhance reporting, and deliver scalable, production-ready feature engineering code.
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   Drives engagement with business stakeholders, effectively communicating complex technical concepts in a clear, accessible manner to align analytics engineering initiatives with strategic goals.
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  Key Skills Required
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 The Senior Analytics Engineer manages data flow in the data lakehouse, ensuring well-structured, high-quality data for analysis and strategic decision-making. Key responsibilities include designing scalable data architectures in conjunction with Domain and Product Data Architects, overseeing data pipeline development, and maintaining data integrity. This role involves collaboration with Domain and Business Data Stewards to align data solutions with organizational objectives. Below are the key technical skills needed by an Senior Analytics Engineer
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   Advanced SQL expertise is essential for querying, transforming, and managing data within databases to support business insights. Proven experience in developing and optimising ETL/ELT pipelines, particularly with tools like DBT, ensures efficient data transformation and modelling.
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   A strong understanding of data modelling techniques, including star and snowflake schemas, is critical for structuring data for analysis. Proficiency in cloud platforms, such as AWS and GCP, with hands-on experience in services like Databricks, Redshift, BigQuery, and Snowflake, is highly valued.
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   Advanced Python skills for data manipulation, automation, and scripting, using libraries like Pandas and NumPy, are necessary for effective data engineering. Expertise in managing and optimising data architectures within data warehouse and lakehouse environments is a core requirement.
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   Proficiency in version control tools like Git ensures effective collaboration and management of code and data models. Experience with workflow automation tools, such as Apache Airflow, is crucial for streamlining and orchestrating complex data processes.
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   Skilled at integrating data from diverse sources, including APIs, databases, and third-party systems, ensuring seamless connectivity. A strong commitment to data quality assurance is demonstrated through rigorous validation and monitoring processes throughout the data pipeline.
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   Strong problem-solving abilities are essential for diagnosing and resolving pipeline issues while optimising performance for scalability. Knowledge of analytics platforms, such as Tableau and ThoughtSpot, ensures compatibility with data visualisation and reporting requirements.
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  What You&rsquo;ll Get In Return
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   Competitive base salary
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   Up to 20% bonus
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   25 days holiday
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   BAYE, SAYE &amp; Performance share schemes
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   7% pension
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   Life Insurance
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   Work Away Scheme
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   Flexible benefits package
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   Excellent staff travel benefits
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  About EasyJet
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 At easyJet our aim is to make low-cost travel easy &ndash; connecting people to what they value using Europe&rsquo;s best airline network, great value fares, and friendly service.
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 It takes a real team effort to carry over 90 million passengers a year across 35 countries. Whether you&rsquo;re working as part of our front-line operations or in our corporate functions, you&rsquo;ll find people that are positive, inclusive, ready to take on a challenge, and that have your back. We call that our &lsquo;Orange Spirit&rsquo;, and we hope you&rsquo;ll share that too.
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  Apply
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 Complete your application on our careers site.
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 We encourage individuality, empower our people to seize the initiative, and never stop learning. We see people first and foremost for their performance and potential and we are committed to building a diverse and inclusive organisation that supports the needs of all. As such we will make reasonable adjustments at interview through to employment for our candidates.
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  Business Area
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 Information Technology (IT)
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 United Kingdom-London-London Luton Airport
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  Organisation
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 Information Technology (IT)
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  Schedule
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 Full-time
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  Unposting Date
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 Ongoing
</div>


Senior Data Analytics Engineer

Haufe Group

<div><div><div><div><div><p>Freiburg</p>
</div><div>ab sofort
</div></div><div><p>F&uuml;r unser Team <b>Data &amp; Analytics Services</b> im Gesch&auml;ftsbereich IT suchen wir <b>zum n&auml;chstm&ouml;glichen Termin</b> am <b>Standort Freiburg</b> eine:n <b>Senior Data Engineer (Lead, Principal) &ndash; Snowflake AWS &amp; Analytics (d/m/w)</b>.</p>
</div><h3 class="jobSectionHeader"><b>DAS ERWARTET DICH:</b></h3>
<div><div><p>Als <b>Senior Data Engineer </b>mit <b>Spezialisierung in Snowflake und AWS</b> wirst du robuste und cloud-native Snowflake-L&ouml;sungen auf Enterprise-Niveau entwerfen und implementieren. Diese <b>hands-on Engineering-Position </b>hat signifikanten architektonischen Einfluss wirkt als technischer Gegenpol zu Data Architects. Du arbeitest intensiv mit <b>Snowflake, AWS, dbt</b> und anderen modernen Datenwerkzeugen.</p>
<p><b>Deine Kernaufgaben:</b></p>
<ul><li><b>Snowflake Platform Engineering: </b>Account-Setup, Warehouse, Performance-Optimierung</li>
<li><b>Cloud Integration &amp; Data Pipelines: </b>u.a. ELT z.B. mit Fivetran/dbt, Snowpipe, AWS S3/Stages</li>
<li><b>Governance Implementation:</b> DQ-Tests (dbt), Tagging/Masking Policies, Data Contracts</li>
<li><b>Self-Service Enablement: </b>Analytics Engineering Patterns, Data Products</li><br>
</ul></div></div><p></p><h3 class="jobSectionHeader"><b>DAS BRINGST DU MIT:</b></h3>
<div><div><p><b>Dein Profil:</b></p>
<ul><li>Bachelor-Abschluss in Data Science, Computer Science, Engineering oder einem verwandtem Bereich</li>
<li>Mindestens 4 Jahre Erfahrung als Data Engineer (d/m/w) mit Fokus auf Cloud-Datenarchitekturen</li>
<li>Sehr gute Deutsch Kenntnisse und flie&szlig;ende English Kenntnisse (C1) in Wort und Schrift runden dein Profil ab</li>
</ul><p><b>Technische Expertise (Must-Have):</b></p>
<ul><li>Snowflake-AWS-Integration: u.a. Architektur, RBAC, Performance-Tuning, S3, IAM</li>
<li>Daten-Ingestion: ELT-Plattformen (z.B.Fivetran, Stitch, Snowpipe)</li>
<li>SQL &amp; Datenmodellierung: SQL, dbt, dimensionale Modellierung und Data Vault</li>
<li>Programmierung: Python f&uuml;r Datenverarbeitung und Automatisierung</li>
<li>DataOps: Analytics Engineering, Data Mesh und Self Service Principles</li>
</ul><p><b>Nice-to-have:</b></p>
<ul><li>Deployment Backbone: Terraform inkl. Versioning, State-Management ggf. GitOps-Workflows</li>
<li>Verst&auml;ndnis von Data- Management und Data-Governance-Frameworks sowie Datenqualit&auml;t.</li>
<li>Erfahrung mit Datenvalidierung, Testmethodologien (dbt tests)</li>
<li>Orchestrierung &amp; DevOps: Airflow/Dagster, CI/CD, Git-Workflows.</li>
<li>Vertrautheit mit Visualisierungstools unter anderem: Tableau, Power BI, Streamlit</li>
<li>Zertifizierungen oder gleichwertige Erfahrung wie Snowflake SnowPro, AWS, Terraform</li>
</ul><p><b>Was wir bieten</b></p>
<ul><li>Du wirst Teil eines nationalen und internationalen Netzwerks von Datenprofis und profitierst von kontinuierlicher Weiterbildung durch unsere Haufe Akademie</li>
<li>Eine Kultur, die Freiheit und Verantwortung sch&auml;tzt und Innovationen vorantreibt</li>
<li>Ein inklusives Arbeitsumfeld, das Vielfalt und Chancengleichheit f&ouml;rdert und Menschen aus allen Hintergr&uuml;nden unterst&uuml;tzt</li><br>
</ul><p></p><p>#haufegroup<br>
<br>
</p><br>
<br>
Job ID: REF381H</div></div></div></div></div>
<br><div><h3 class="jobSectionHeader"><b>Maresa Kindle</b></h3>
<div>Bewerbungen bitte nur &uuml;ber unser Online-Formular absenden, welches du &uuml;ber den Button &bdquo;Jetzt bewerben&ldquo; erreichst.</div></div>
<br><div><div><div><h2 class="jobSectionHeader"><b>Unsere Benefits:</b></h2>
</div><div><div><div><h3 class="jobSectionHeader"><b>Pers&ouml;nliches Onboarding</b></h3>
<p>Onboarding-App, Welcome Days und -Bag, Campustour, Buddy-Programm</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Wegweisendes Arbeitsmodell</b></h3>
<p>Hybride Zusammenarbeit als Kombination aus B&uuml;ropr&auml;senz und Homeoffice, flexible Arbeitszeiten, flache Hierarchien, hohe Eigenverantwortung.</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Nachhaltige Mobilit&auml;t</b></h3>
<p>Jobrad, Mietrad-Station, E-Lades&auml;ulen, Bike-Checks und Zuschuss zum &Ouml;PNV</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Vorsorge</b></h3>
<p>Attraktives Wertguthabenmodell und betriebliche Altersvorsorge</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Choose your device</b></h3>
<p>Wir statten dich mit State of the Art Hard- und Software aus.</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Food &amp; Services</b></h3>
<p>Kaffee und Tee gratis, g&uuml;nstiges und mehrfach ausgezeichnetes Betriebsrestaurant, Packstation auf dem Campus</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Gesundheit &amp; Gemeinschaft</b></h3>
<p>Gesundheitsportal, Hansefit, Gesundheitschecks, standort&uuml;bergreifende Weihnachtsfeier, Sport-Events und -Gruppen, Gymnastikraum, Tischkicker, Billard, Tischtennis, Band-Proberaum</p>
</div></div><div><div><h3 class="jobSectionHeader"><b>Lernen &amp; Entwicklung</b></h3>
<p>Es gibt zahlreiche Initiativen zu Produktentwicklung, Knowledge Sharing oder zu neuen Technologien. Teams organisieren Brown Bag Sessions, Hackathons, gehen auf Events und Meetups. Wir geben Raum f&uuml;r gemeinsames Lernen und f&ouml;rdern deine Weiterentwicklung.</p></div></div></div></div></div>
<br><div><div><div><div><h2 class="jobSectionHeader"><b>Unsere Arbeitsweise:</b></h2>
</div><p></p><div><div><div><div><div><div><div><div><div>3/4</div>
</div></div></div></div><div><div><div><div><div>4/4</div>
</div></div></div></div><div><div><div><div><div>1/4</div>
</div></div></div></div><div><div><div><div><div>2/4</div>
</div></div></div></div><div><div><div><div><div>3/4</div>
</div></div></div></div><div><div><div><div><div>4/4</div>
</div></div></div></div><div><div><div><div><div>1/4</div>
</div></div></div></div><div><div><div><div><div>2/4</div>
</div></div></div></div><div><div><div><div><div>3/4</div>
</div></div></div></div><div><div><div><div><div>4/4</div>
</div></div></div></div></div></div></div><p></p><div><div><div><div><div><div><div><h3 class="jobSectionHeader"><b>Networking</b></h3>
<div><p>Communities of Practice erlauben uns, das Wissen unserer Organisation sichtbar und transparent zu machen. Sie sind eine Plattform, um effizienter zu lernen und uns gemeinsam weiterzuentwickeln. So sichern wir uns unseren Erfolg.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Ownership</b></h3>
<div><p>Bei uns gilt: You build it, you own it. Das Erfolgsrezept f&uuml;r gro&szlig;artige Software sind Teams, die Verantwortung &uuml;bernehmen. Wir setzen auf eine starke und agile Zusammenarbeit, die es erm&ouml;glicht, Produkte selbstst&auml;ndig voranzutreiben.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Kundenzentrierung</b></h3>
<div><p>Wir arbeiten f&uuml;r den Erfolg unserer Kundinnen und Kunden und fokussieren uns auf ihre Bed&uuml;rfnisse. Wir sind agil, leidenschaftlich und handeln pragmatisch, um stets die beste L&ouml;sung f&uuml;r sie zu finden.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Evolution</b></h3>
<div><p>Wir sind eine vielseitige Tech-Community. Von Cloud Computing bis Machine Learning decken wir von bew&auml;hrten bis hin zu State-of-the-Art Technologien vieles ab und entwickeln uns immer weiter.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Networking</b></h3>
<div><p>Communities of Practice erlauben uns, das Wissen unserer Organisation sichtbar und transparent zu machen. Sie sind eine Plattform, um effizienter zu lernen und uns gemeinsam weiterzuentwickeln. So sichern wir uns unseren Erfolg.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Ownership</b></h3>
<div><p>Bei uns gilt: You build it, you own it. Das Erfolgsrezept f&uuml;r gro&szlig;artige Software sind Teams, die Verantwortung &uuml;bernehmen. Wir setzen auf eine starke und agile Zusammenarbeit, die es erm&ouml;glicht, Produkte selbstst&auml;ndig voranzutreiben.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Kundenzentrierung</b></h3>
<div><p>Wir arbeiten f&uuml;r den Erfolg unserer Kundinnen und Kunden und fokussieren uns auf ihre Bed&uuml;rfnisse. Wir sind agil, leidenschaftlich und handeln pragmatisch, um stets die beste L&ouml;sung f&uuml;r sie zu finden.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Evolution</b></h3>
<div><p>Wir sind eine vielseitige Tech-Community. Von Cloud Computing bis Machine Learning decken wir von bew&auml;hrten bis hin zu State-of-the-Art Technologien vieles ab und entwickeln uns immer weiter.</p>
</div></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Networking</b></h3>
<div><p>Communities of Practice erlauben uns, das Wissen unserer Organisation sichtbar und transparent zu machen. Sie sind eine Plattform, um effizienter zu lernen und uns gemeinsam weiterzuentwickeln. So sichern wir uns unseren Erfolg.</p></div></div></div></div></div></div></div></div></div></div></div></div><div></div>

Senior Data Engineer (d/m/w) Snowflake AWS & Analytics

Bloomberg

<div>
 Location
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 London
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 Business Area
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 Engineering and CTO
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 Ref #
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 10049302
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 <strong>
  Description &amp; Requirements
  <br/>
  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
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 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
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 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
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 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
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 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
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 <strong>
  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
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 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
  </li>
  <li>
   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
  </li>
  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
  </li>
  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
  </li>
  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
  <br/>
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 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
  </li>
  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
  </li>
  <li>
   Previous experience with modern CI/CD tools and GitOps workflows
  </li>
  <li>
   Familiarity with implementing automation for model development lifecycles
  </li>
  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
  </li>
  <li>
   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 <br/>
 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
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 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


Senior ML Platform Engineer - Artificial Intelligence

Deloitte

<p></p><div><div><div><div><div><div><div><div><p><b>Data Analytics Engineer </b><b>&ndash; </b><b>Software Engineer II</b></p><p><b>
Role Overview</b><b>:</b> We are seeking a proactive and solutions-oriented <b>Data Analyst</b> with 2.5&ndash;4 years of hands-on experience in data analytics and applied AI/ML techniques. In this role, you will leverage your strong technical foundation and business acumen to transform complex datasets into meaningful insights that guide decision-making and strategy. You will demonstrate expertise in modern data analytics tools (such as Python, SQL) and show enthusiasm for learning next-generation analytics platforms like Adobe Customer Journey Analytics (CJA). The ideal candidate is passionate about turning data into value, comfortable collaborating across diverse teams, and committed to staying at the forefront of emerging analytics and AI trends. You excel at translating business needs into actionable analysis, communicating findings effectively to technical and non-technical audiences, and driving measurable outcomes through data.</p><p></p><p><b>
Work you will do</b></p><ul><li>
Conduct data analysis and prepare reports to support business decision-making using statistical and machine learning techniques.
</li><li>Utilize Python and/or R, along with AI-powered coding tools such as Cursor AI or GitHub Copilot, to accelerate scripting and enhance analytics workflows.
</li><li>Extract, clean, and transform data from various sources&mdash;applying SQL and data wrangling skills to ensure data quality and readiness for analysis.
</li><li>Collaborate with team members to understand data requirements, ensure alignment to business objectives, and contribute to project deliverables.
</li><li>Participate in requirements gathering and solution workshops with stakeholders and senior analysts.
</li><li>Communicate analytical findings clearly to both technical and non-technical audiences via presentations, dashboards, or written summaries.
</li><li>Demonstrate curiosity and initiative by proactively learning new tools and technologies, such as Adobe Customer Journey Analytics (CJA), Adobe Experience Platform (AEP), and similar digital analytics solutions.
</li><li>Support ongoing enhancements to analytics processes, documentation, and team best practices.
</li><li><ul><li>oriented team culture by sharing knowledge and supporting others.</li></ul></li></ul><p></p><p><b>
Key Responsibilities</b><b>:</b></p><p><b>
Outcome-Driven Accountability: </b>Aligns with: Delivering business outcomes, transforming business needs into analytical solutions, upholding quality in analytics and code as stated in your technical and professional skills.</p><p><b>
Technical Leadership and Advocacy: </b>Aligns with: Supporting technical best practices, code integrity, and active participation in key SDLC phases (requirement analysis, development, testing) in Python/R, SQL, and relevant analytics tasks. Collaboration with senior team members aligns well with the CL3 role.</p><p><b>
Engineering Craftsmanship: </b>Aligns with: Clean code, adherence to standards, data wrangling, preparing documentation, and commitment to best practices. Directly supports your expectations for &ldquo;Programming,&rdquo; &ldquo;Data Wrangling,&rdquo; and &ldquo;AI Coding Assistants&rdquo; skills, and continuous learning.</p><p><b>
Customer-Centric Engineering: </b>Aligns with: Focus on delivering what stakeholders need, rapid prototyping, experimentation, and direct engagement with business/product teams, reflecting &ldquo;Analytical Thinking&rdquo; and &ldquo;Ability to transform business needs into analytical solutions&rdquo;.</p><p><b>
Incremental and Iterative Delivery: </b>Aligns with: Agile methodologies, growth mindset, and continuous improvement. Supports &ldquo;Commitment to continuously improving analytics workflows&rdquo; and your requirement for contributing to maintainable, supportable solutions.</p><p><b>
Cross-Functional Collaboration and Integration: </b>Aligns with: Collaboration, working with diverse teams, and integrating multiple perspectives. Matches &ldquo;Collaboration,&rdquo; &ldquo;Communication,&rdquo; and &ldquo;Working across functions and with diverse teams.&rdquo;</p><p><b>
Advanced Technical Proficiency: </b>Aligns with: Python/R for analytics and ML, SQL, AI coding assistants, adopting new analytics tools like Adobe CJA, and embracing SDLC and Agile practices. Encourages continuous technical improvement per your &ldquo;Willingness to learn&rdquo; and &ldquo;Technical Skills&rdquo; requirements.</p><p><b>
Domain Expertise: </b>Aligns with: Quickly acquiring business-relevant knowledge, understanding data designs, and supporting business use cases with technical solutions. Supports &ldquo;Domain knowledge,&rdquo; &ldquo;Transform business needs into analytical solutions,&rdquo; and related technical skills.</p><p><b>
Effective Communication and Influence: </b>Aligns with: Excellent communication skills, presenting complex ideas to varying audiences (technical/non-technical), and contributing to team and stakeholder discussions.</p><p><b>
Engagement and Collaborative Co-Creation: </b>Aligns with: Building strong team and stakeholder relationships, collaborative mindset, and co-creation of value-driven analytics/workflows&mdash;underpinning &ldquo;Collaboration,&rdquo; &ldquo;Participation in hackathons,&rdquo; and your supportive team culture.</p><p></p><p><b>
The team</b><b>:</b> US Deloitte Technology Product Engineering drives Deloitte&rsquo;s success by delivering innovative analytics and data science solutions through a modern, scalable, and value-focused delivery model. As the firm&rsquo;s premier internal development team, we empower business units and internal operations to make smarter, data-driven decisions by transforming complex business needs into actionable insights and robust digital products. Leveraging advanced analytics tools, machine learning, and a responsive talent structure, our team consistently delivers measurable outcomes that enhance Deloitte&rsquo;s efficiency, effectiveness, and market leadership&mdash;upholding our tradition of excellence and commitment to impactful results.</p><p></p><p><b>
Key Qualifications</b><b>:</b></p><ul><li>
2.5&ndash;4 years of professional experience in data analytics or data science
</li><li>Proficiency in Microsoft Fabric and SAC</li><li>
Proficiency in Python and/or R for analytics and machine learning
</li><li>Strong SQL skills for data querying and transformation
</li><li>Hands-on experience with AI-powered coding tools (e.g., Cursor AI, GitHub Copilot)
</li><li>Excellent communication and collaboration skills
</li><li>Ability to transform business needs into analytical solutions</li></ul><p></p><p><b>
Good to have skills:
</b></p><div><ul><li>Experience with cloud analytics (AWS, Azure, GCP)</li></ul>
</div><p>2. Knowledge on BI tools like Tableau, SAP BOE is preferred</p><div>
<ul><li>Exposure to unstructured data or MLOps</li></ul>
<ul><li>Participation in analytics competitions, hackathons, or holding relevant certifications</li></ul>
<ul><li>Domain knowledge in a relevant business vertical</li></ul>
</div><p></p><p><b>How You will Grow:</b></p><ul><li>
Opportunity to work on impactful analytics projects</li><li>
Support for ongoing professional development and learning new technologies</li><li>
Collaborative environment with experts across analytics and business domains</li></ul></div><br>
<p></p>
</div><div><div><div><b>Our purpose</b></div><br>
<div></div>
Deloitte&rsquo;s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities.</div>
</div><div><div><div><b>Our people and culture</b></div><br>
<div></div>
Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas and perspectives, and bring more creativity and innovation to help solve our clients&rsquo; most complex challenges. This makes Deloitte one of the most rewarding places to work.</div>
</div><div><div><div><b>Professional development</b></div><br>
<div></div>
At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India.</div>
</div><div><div><b>Benefits to help you thrive</b><br>
</div><div>
At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially&mdash;and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you.</div><div></div>
</div><div><div><b>Recruiting tips</b></div><br>
<div></div>
From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters.
</div></div></div></div></div></div><div><div><div><p>Requisition code: 357466</p></div></div></div></div>

Data Analytics Engineer - Software Engineer II

Rapid Data GmbH

<div><h4 class="jobSectionHeader"><b>Job Description</b></h4><p>
Own the technical vision and execution strategy for our data platform across DACH and Nordics (Funeral ERP, Marketplace &amp; Memorials), in partnership with the CTO who carries the cross-functional org-design conversation. A hands-on senior IC role: you set target-state architecture, make the tooling calls (Matomo, Power BI, Redash, Boomi), own GDPR documentation, and ship the first version of every layer yourself, from event schema and pipelines through to KPI dashboards. You work alongside one Data &amp; Analytics Engineer, use Cursor, GitHub Copilot, LLM-assisted SQL, and AI-augmented analytics as the default mode of delivery, not exceptions, and have a clear path to Head of Data &amp; Analytics as the function scales beyond three people.</p><h4 class="jobSectionHeader"><b><br>
Your tasks:</b></h4><p></p><ul><li>
Assess the current data services and architecture, define a coherent target-state, and lead the migration</li><li>
Own the data and analytics strategy across DACH and Nordics, including the target-state tooling decision (Matomo, Power BI, Redash) and the role of Boomi in our integration layer.</li><li>
Define and govern core product and business metrics; build production-grade KPI dashboards and self-service BI in Power BI with pipeline freshness and anomaly alerting</li><li>
Design and deliver end-to-end B2C analytics dashboards covering the full user journey across our consumer products (memorial portals, donation application, flower shop / e-commerce) across acquisition, activation, conversion, and retention, as the single trusted view for Product and Commercial stakeholders</li><li>
Instrument and govern event tracking across all products and B2C touchpoints (memorial portals, donation application, flower shop / e-commerce); currently Matomo: funnel events, custom dimensions, hashed IDs, IP anonymisation, with a unified user identity scheme that traces users end-to-end across domains, versioned tracking plans, and QA checks</li><li>
Own GDPR documentation and data governance (personal-data inventory, DPA register, audit trail, deletion process), and the quality/security standards across the platform</li><li>
Make build-vs-buy and vendor calls (Boomi, offshore analytics resourcing) and input to the CTO on team-growth sequencing as the roadmap demands.</li></ul><p></p><h4 class="jobSectionHeader"><b>
Your skillset:</b></h4><p></p><ul><li>
Vast experience in data, with 4+ years at senior/staff/principal level in analytics or data engineering in a SaaS environment; degree in a numerate or computing discipline, or equivalent practical experience.</li><li>
Genuinely AI-native: you use Cursor, GitHub Copilot, LLM-assisted SQL, and AI-augmented analytics as standard tools in your day-to-day work, not as occasional aids.</li><li>
Proven track record building large-scale data infrastructure (warehouses, lakes, ELT/ETL) and shipping production-grade BI end-to-end.</li><li>
Hands-on with event-based analytics instrumentation (Matomo, Segment, Snowplow, Amplitude or equivalent), cross-domain user identity and session tracking, and e-commerce funnel analytics; proven ability to design a unified tracking plan across multiple B2C products and with metric definition and governance at scale.</li><li>
Expert SQL, working Python (or R); fluent with the modern data stack (dbt, Spark, or similar) and at least one BI platform (Power BI preferred).</li><li>
Comfortable owning GDPR documentation, data quality and anomaly monitoring, and A/B testing.</li><li>
Fluent English &amp; German ; Nordic language a plus.</li></ul><p></p><h4 class="jobSectionHeader"><b><br>
What we offer:</b></h4><p></p><ul><li>
Real autonomy to set the technical direction and choose the target-state tooling stack, with a clear path to Head of Data &amp; Analytics as the function scales</li><li>
Hands-on work alongside Engineering and Product, with daily AI-assisted delivery as the default mode</li><li>
Direct line to the CTO and visibility with the wider executive team</li><li>
A Berlin office that keeps you close to Engineering, Product, and the rest of the business</li><li>
Meaningful work as the market leader in funeral technology, across Germany and Nordics</li></ul><p></p><h4 class="jobSectionHeader"><b>
About us</b></h4><p></p><p>
Rapid Data is a leading software provider for the funeral industry in Europe and has been synonymous with innovation and progress since 1989. It is our passion to develop state-of-the-art ERP and CRM solutions that revolutionize the way funeral service providers work.</p><p>
We are more than just a company &ndash; we are pioneers of change and stand at the forefront to lead the industry into a new era. Our goal is not only to be present in Europe but to establish a global presence, supporting every funeral service provider and their partners with our all-in-one technology platform.</p><p>
Driven by our vision and supported by one of the most demanding and renowned private equity investors in the world, we are in a phase of accelerated growth. Every day is a new opportunity for us to push our boundaries and realize our dreams. We are ready to change the world &ndash; be part of this exciting journey with Rapid Data.</p></div><p></p>

Principal Data & Analytics Engineer (m/w/d)

LimeFlight

<div><p>Join our fully remote, mission-driven team dedicated to pioneering <b>sustainable inflight service management</b>. Work on innovative technology solutions with global impact, collaborate within a diverse, international environment, and continuously enhance your skills through ongoing learning opportunities.</p><p></p><p>
Headquartered in Zurich, Switzerland with team members across 11 countries, we offer a dynamic and engaging company culture that celebrates creativity, collaboration, and inclusion.
</p><h4 class="jobSectionHeader"><b>About the role</b></h4><p>
We are hiring a <b>Senior Data &amp; Analytics Engineer</b> to take <b>end-to-end ownership of our data platform and BI layer</b>.</p><p></p><p>
We are on a mission to contribute to a <b>zero-waste future</b> by drastically reducing food waste, fuel consumption, costs, and most importantly, <b>CO₂ emissions</b> in the airline industry. Every role in our company is a direct contributor to this vision - and as a <b>Senior Data &amp; Analytics Engineer</b> you will be at the forefront of turning data into meaningful insights, empowering our customers to effectively use them and drive real impact.</p><p></p><p>
You will evolve a vendor-built BI solution into a <b>modern, product-grade data platform</b> and ensure that data is transformed into <b>scalable, trusted, and actionable insights</b> for both our customers and internal teams. You&rsquo;re not just building dashboards, you&rsquo;re enabling better decisions and measurable impact.</p><p></p><p>
This role combines:</p><ul><li><b>
Data Engineering</b> (pipelines, processing, customer facing exports, platform)</li><li><b>
Analytics Engineering</b> (modeling, KPIs, semantic layer)</li><li><b>
Data Product Ownership</b> (customer impact, insight generation)</li></ul><h4 class="jobSectionHeader"><b>
What You&rsquo;ll Own</b></h4><p><b>
Platform, Architecture &amp; Pipelines</b></p><p>
Own the end-to-end data platform (<b>Databricks </b>and <b>Microsoft Fabric</b>)</p><ul><li>
Design and operate scalable pipelines and lakehouse architecture</li><li>
Build scalable ETL/ELT workflows and manage batch/near real-time processing</li><li>
Ensure data quality, reliability, observability, and performance</li><li>
Define standards, data contracts, and architecture principles (clean, modular, scalable data platform)</li><li>
Optimize cost (e.g. Databricks jobs) and workload distribution across platforms</li></ul><p><b>
Data Modeling &amp; Semantic Layer</b></p><ul><li>
Own <b>Power BI </b>semantic models and KPIs</li><li>
Build clean, scalable dimensional models (star schema)</li><li>
Ensure performance and consistency of DAX, aggregations, and dataset refresh</li></ul><p><b>
Customer-Facing Analytics</b></p><ul><li>
Build and maintain customer-facing dashboards and embedded analytics</li><li>
Ensure consistent and trusted metrics across all outputs</li><li>
Enable self-service analytics with governance</li><li>
Maintain and monitor customer facing exports</li></ul><p><b>
Data as Product</b></p><ul><li>
Translate business and customer needs into scalable data solutions</li><li>
Define KPIs and reporting standards with Product</li><li>
Proactively build insights and identify opportunities to create additional customer value</li><li>
Drive measurable customer and business impact</li></ul><p><b>
Platform Quality, Operations, Security &amp; Governance</b></p><ul><li>
Build necessary validation scripts, unit tests, data quality checks</li><li>
Implement CI/CD, testing, and versioning for pipelines and BI</li><li>
Support multi-tenant architecture, security, and governance</li><li>
Implement monitoring and alerting (pipelines, refreshes)</li></ul><p><b>
Migration &amp; Insourcing (Initial Focus)</b></p><ul><li>
Take ownership of a vendor-built BI solution</li><li>
Reverse-engineer pipelines, logic, and reports</li><li>
Reduce technical debt and rebuild toward a clean architecture</li></ul><h4 class="jobSectionHeader"><b>
What We&rsquo;re Looking For</b></h4><p><b>
Experience</b></p><ul><li>
5+ years in data engineering / analytics engineering for customer-facing BI products</li><li>
Experience in SaaS or product-driven environments</li><li>
Proven track record building scalable data platforms and customer-facing analytics</li></ul><p><b>
Technical &amp; Platform Skills</b></p><ul><li>
Strong experience with:<ul><li>
Databricks (Spark / PySpark, Delta Lake)</li><li>
Microsoft Fabric or Azure data stack</li><li>
Power BI (data modeling, DAX, performance)</li></ul></li><li>
Advanced SQL and dimensional modeling (Kimball) expertise</li><li>
Lakehouse architecture &amp; ETL/ELT design</li><li>
Multi-tenant data models &amp; embedded analytics</li></ul><p><b>
Engineering Practices</b></p><ul><li>
CI/CD for data pipelines and BI assets</li><li>
Write reusable, modular, maintainable and testable code.</li><li>
Monitoring and data quality practices</li><li>
Version control (e.g., Git)</li></ul><p><b>
Nice-to-have</b></p><ul><li>
Azure infrastructure knowledge (IAM, networking)</li><li>
Data quality/testing frameworks (e.g., Great Expectations)</li></ul><p><b>
Mindset</b></p><ul><li>
Strong ownership and autonomy: You take full ownership of outcomes, not just tasks</li><li>
Impact-driven: You focus on real-world results and have strong intuition for identifying patterns, anomalies, and optimization opportunities</li><li>
Product thinker: You connect data to user value and turn raw data into clear, actionable insights</li><li>
Proactive: You proactively identify opportunities, validate ideas, and build reports, dashboards, and analyses without waiting for requirements.</li></ul><ul><li>
Domain expert: You understand business contexts quickly and translate problems into effective data solutions.</li><li>
Pragmatic: You prioritize simplicity and avoid overengineering, focusing on what delivers value.</li><li>
Clear communicator: You communicate effectively across technical and business stakeholders, making complex topics easy to understand.</li></ul><h4 class="jobSectionHeader"><b>
Language</b></h4><p>
Min. English C1</p><h4 class="jobSectionHeader"><b>
Expected travel needs</b></h4><p>
2 annual one-week team events</p><h4 class="jobSectionHeader"><b>
Our Tech Stack</b></h4><ul><li>
C# (.NET 8&ndash;10), ASP.NET Core, Entity Framework Core</li><li>
Microsoft SQL Server, Azure Blob Storage</li><li>
Azure App Services &amp; Functions, Docker</li><li>
Azure Service Bus, Terraform</li><li>
GitHub Actions, SonarQube, extensive unit &amp; integration tests</li><li>
Angular Latest Version</li><li>
Databricks and Azure Fabric</li></ul><h4 class="jobSectionHeader"><b>
Hiring Process</b></h4><ul><li>
Recruiter Screen (45 mins)</li><li>
Interview with the Hiring Manager (1 hour)</li><li>
Technical interview (1 hour)</li><li>
Discussion with founder(s) and peer(s) (1 hour)</li></ul><p><b><br>
LimeFlight is proud to be an equal opportunity employer.</b></p><p>
We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work.</p><p></p><p>
Join us and be part of a team committed to shaping a zero-waste future for aviation, where your ideas and passion truly matter.</p><p></p><p>
Let&rsquo;s talk!</p></div>

Senior Data & Analytics Engineer (Europe, 100% remote)

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