data analytics engineer

Discovery Education

We are looking for a highly skilled Data Analytics Engineer to support product analytics, product marketing, customer support, and operational teams. This role enables data-driven decision-making by developing scalable data models and delivering high-quality insights across the business. The position works cross-functionally with engineering, data science, and business stakeholders and plays a key role in ensuring the accessibility, quality, and reliability of data.
 The successful candidate will become a specialist in our modern data stack, including Snowflake, dbt, Looker, and Hightouch, and will contribute to building a robust analytics capability at scale.
 
In This Role You Will: 
Data Modeling & Engineering
 <ul>
<li>Build and maintain scalable data models using dbt and Snowflake</li>
<li>Transform raw data into clean, reliable datasets for analysis</li>
<li>Apply engineering best practices to analytics code to ensure scalability and maintainability</li>
</ul>
Insight & Business Impact
 <ul>
<li>Translate data models into actionable insights for stakeholders across product, marketing, and operations</li>
<li>Partner with business teams to define analytics requirements and measurable success outcomes</li>
</ul>
Collaboration & Stakeholder Engagement
 <ul>
<li>Work collaboratively with data engineers, data scientists, and business stakeholders</li>
<li>Support cross-functional teams by delivering high-quality data solutions</li>
</ul>
Data Governance & Quality
 <ul>
<li>Maintain data documentation, definitions, and lineage</li>
<li>Advocate for and uphold data quality and coding standards through code reviews</li>
</ul>
Tools & Technology
 <ul>
<li>Utilise Snowflake, dbt, Looker, Git, and modern data tooling to deliver analytics solutions</li>
</ul>
Core Competencies for Success: 
<ul>
<li>Collaborates – Builds strong partnerships across technical and business teams to achieve shared outcomes</li>
<li>Drives Results – Consistently delivers high-quality outputs in a fast-paced, data-driven environment</li>
<li>Ensures Accountability – Takes ownership of data quality, accuracy, and delivery standards</li>
<li>Tech Savvy – Adopts and applies modern data technologies to improve efficiency and scalability</li>
<li>Manages Complexity – Analyses complex datasets and translates them into clear, actionable insights</li>
</ul>
Credentials and Experience: 
<ul>
<li>3+ years of experience in a data analyst, analytics engineer, data engineer, or similar role</li>
<li>2+ years of experience working with product and/or customer data</li>
<li>3+ years of hands-on experience writing and optimising SQL for data analysis and transformation</li>
<li>Experience using Python, R, or similar tools for data analysis and manipulation</li>
<li>1–3 years of experience working with modern data warehouses and transformation tools (e.g., Snowflake, dbt)</li>
<li>Experience transforming raw data into clean, production-ready datasets and maintaining technical documentation</li>
<li>Experience working with large-scale datasets (e.g., high-volume event or behavioural data)</li>
<li>Exposure to API integrations and data ingestion processes is desirable</li>
<li>Demonstrated ability to work effectively in a remote or distributed team environment</li>
<li>Legal right to work in the United Kingdom</li>
</ul>
This role is hybrid based in Bath, UK. As the office is a listed building, we do not have a lift so please make us aware so we can make necessary accommodations.
 The hiring range for this position is between £35,000 - £39,400 annually, however, base pay offered may vary depending on job-related knowledge, skills, experience, and location. Additionally, this position is eligible for an Annual Bonus.
 
-----
 
At Discovery Education, we are fulfilling our mission of preparing learners for tomorrow by creating innovative classrooms connected to today's world.
 
Serving more than 4.5 million educators and 45 million students, available in approximately half of U.S. classrooms and primary schools in the UK, and more than 140 countries around the globe; we are on a journey to transform teaching and learning though innovative partnerships with school districts, states, ministries of education, and other like-minded organizations.
 
We have built an award-winning and highly reputable organization because of talented and driven people who work together to accelerate student achievement by tapping into students' natural curiosity and desire to learn by capturing their minds and imagination through the fascination of Discovery.
 
Why Join Discovery Education?
 Discovery Education believes empowering each team member is vital to cultivating high performing, highly engaged teams. Being a part of our team means we partner together to achieve mutual goals. To this end, Discovery Education offers inclusive and robust offerings. You can find a complete listing on our Career Page.
 
Team Member Wellness – When you feel great, you do great work!
 <ul>
<li>28 days leave plus UK bank holidays</li>
<li>Annual Winter Holiday Break (typically the last week of December)</li>
<li>Income protection to support you during long term illness</li>
<li>4x salary Life Assurance</li>
<li>Medicash cash back plan</li>
<li>Private Medical Insurance</li>
<li>Vivup cash back and discounted plan for 1000s of high street stores</li>
<li>Cycle to work scheme</li>
<li>Paid eye test and money towards glasses</li>
<li>Numerous Employee Assistance Programs</li>
<li>A social committee that helps us team build and celebrate wins</li>
</ul>
Career Development Ownership - Be the driver of your success!
 <ul>
<li>Continuing Education AND Tuition Reimbursement Programs for when you choose to study further in your field as you work</li>
<li>Mentorship program and collaboration with veteran leaders</li>
<li>Constant opportunities for cross-functional training and skill building</li>
<li>Uncapped career growth</li>
<li>Unlimited LinkedIn Learning</li>
<li>Leadership training for people mangers</li>
</ul>
This opportunity is perfect for people interested in joining a high-performing, collaborative team, who enjoy a dynamic industry, and are excited about high-impact, project-based work.
 
Inspired? We would love the opportunity to review your candidacy! Select the blue “Apply Now” button at the bottom left of the screen to begin your application.
 
Discovery Education is an equal opportunity employer. Discovery Education is committed to being an employer of choice, not just a good place to work, but a great and inclusive place to work. To that end, we strive to recruit and maintain a workforce that meaningfully represents the communities we serve. Qualified applicants will receive consideration for employment without regard to their race, color, religion, national origin, sex, sexual orientation, gender, protected veteran status or disabled status or, genetic information.

Data Analytics Engineer

Henkel

<div><div><h4 class="jobSectionHeader">About this Position
</h4>In this role, you will design and build scalable data assets and analytical solutions that enable data-driven decision-making across BI Team. 
 
 
<h4 class="jobSectionHeader">What you&acute;ll do
</h4><ul><li>Design, build, and maintain analytical data models and cubes (e.g., Azure Analysis Services / semantic models) to support reporting and advanced analytics</li><li>
Develop scalable data pipelines on Databricks using Python and Spark to transform raw data into trusted data assets</li><li>
Build and manage end-to-end data assets, from ingestion to curated datasets ready for BI consumption</li><li>
Ensure data quality, consistency, and performance optimization across analytics solutions</li><li>
Collaborate closely with business stakeholders, analysts, and data teams to translate requirements into scalable solutions</li><li>
Contribute to modern analytics architecture, best practices, and reusable frameworks</li><li>
Leverage AI-powered tools (e.g., Copilot, Genie, LLM-based solutions) to improve development efficiency and explore new use cases</li><li>
Continuously explore new technologies and proactively drive improvements within the data landscape</li>
</ul><h4 class="jobSectionHeader">What makes you a good fit
</h4><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or a related field</li><li>
3&ndash;5 years of experience in data engineering / analytics engineering</li><li>
Strong hands-on experience with Python &amp; PySpark, Databricks (highly preferred), SQL &amp; data modeling (dimensional modeling is a plus)</li><li>
Experience building and maintaining analytical models / semantic layers (e.g., cubes, tabular models, Analysis Services, Power BI models)</li><li>
Familiarity with Spark-based data processing frameworks</li><li>
Experience working with Git and collaborative development workflows (CI/CD is a plus)</li><li>
Strong understanding of end-to-end data pipelines and data lifecycle</li><li>
Interest or experience in AI-driven development (GenAI, copilots, automation tools)</li>
</ul><h4 class="jobSectionHeader">Some perks of joining Henkel
</h4><ul><li>Flexible work scheme with flexible hours, hybrid work model, and work from anywhere policy for up to 30 days per year</li><li>
Diverse national and international growth opportunities</li><li>
Global wellbeing standards with health and preventive care programs</li><li>
Gender-neutral parental leave for a minimum of 8 weeks</li><li>
Employee Share Plan with voluntary investment and Henkel matching shares</li><li>
Comprehensive Health Insurance for employee + dependents</li><li>
Employee Assistance Programme provides a wide range of mental health and wellbeing benefits</li></ul>
At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We look for a diverse team of individuals who possess different backgrounds, experiences, personalities and mindsets.</div></div>

G&W Electric Company

<div>Data Analytics Engineer I
Position Summary
The Data Analytics Engineer I supports the design, development, maintenance, and optimization of the enterprise analytics data platform. This role assists with data pipelines, data models, integration processes, data quality controls, and analytical capabilities that support reporting, AI initiatives, automation, and enterprise decision making.
The Engineer I works with Data Analytics Engineers, Developers, Analysts, and business stakeholders to ensure enterprise data is reliable, accessible, and usable for analytics solutions. This role is intended for an early-career data engineering professional with strong technical aptitude who can contribute to data integration, data modeling, SQL development, documentation, testing, and platform support while continuing to build deeper expertise in enterprise data architecture and advanced analytics.
Key Responsibilities
<ul><li>Design, develop, test, and maintain data pipelines and integration processes under appropriate guidance.</li>
<li>Build and support data models used for enterprise analytics, dashboards, reporting, and business semantic layers.</li>
<li>Support data ingestion from ERP, CRM, manufacturing, quality, and other operational systems.</li>
<li>Develop and maintain data quality monitoring, validation, and reconciliation processes.</li>
<li>Support Incorta platform architecture, data modeling, performance monitoring, and optimization activities.</li>
<li>Develop SQL scripts, data transformations, and technical solutions to support analytics needs.</li>
<li>Support Python-based automation, analytics, and AI-related solutions.</li>
<li>Assist with machine learning, predictive analytics, and intelligent automation initiatives.</li>
<li>Implement data governance standards, metadata management practices, and technical documentation requirements.</li>
<li>Document data architecture, data lineage, integration processes, technical standards, and support procedures.</li>
<li>Collaborate with Developers and Analysts to ensure data availability, consistency, accuracy, and usability.</li>
<li>Troubleshoot data issues, pipeline failures, performance concerns, and reporting discrepancies.</li>
<li>Build knowledge of enterprise source systems, data architecture, cloud data platforms, AI technologies, and analytics engineering practices.</li>
</ul>
Qualifications
<ul><li>Bachelor&rsquo;s degree in Computer Science, Data Engineering, Information Systems, Analytics, Data Science, or related field.</li>
<li>0&ndash;3 years of experience in data engineering, database development, ETL/ELT development, data integration, analytics engineering, reporting data models, or related technical work.</li>
<li>Strong SQL and database development skills.</li>
<li>Experience with ETL/ELT processes, data modeling, and data transformation.</li>
<li>Strong analytical, troubleshooting, and problem-solving capabilities.</li>
<li>Understanding of data quality, data validation, and reconciliation practices.</li>
<li>Ability to work collaboratively with technical teams and business stakeholders.</li>
<li>Strong attention to detail and commitment to reliable, accurate data.</li>
<li>Ability to learn enterprise platforms, source systems, data architecture, and emerging analytics technologies.</li>
</ul>
Preferred Qualifications
<ul><li>Experience with Incorta.</li>
<li>Experience with Python development.</li>
<li>Familiarity with machine learning and AI technologies.</li>
<li>Exposure to cloud-based data platforms.</li>
<li>Manufacturing and ERP data experience.</li>
<li>Experience with metadata management, data lineage, or data governance practices.</li>
<li>Experience supporting data pipelines for reporting, dashboards, or analytical applications.</li></ul></div>

Data Analytics Engineer I

Hertz

<div>
 
 Design,
 
 build from the ground up
 
 , and govern the end‑to‑end
 
 marketing data foundation
 
 , including tagging, tracking, data pipelines, and modelling, to create a trusted
 
 single source of truth
 
 across brand direct, paid media, social, and CRM.
 
 
 
 
 
 This role is accountable for establishing
 
 greenfield data flows, standards, and operating models
 
 , enabling faster, better decision‑making through accurate data, integrated views (GA4, Salesforce, Databricks, COGNOS), and scalable insight products (dashboards, attribution, MMM). Act as the
 
 primary point of contact
 
 for all digital tracking and marketing data issues, ensuring
 
 reliability, compliance, and speed
 
 across the ecosystem.
 
 
 
 
 
 Own tagging and tracking standards for web/app (GTM, GA4, CM360/Floodlight, Meta pixel/event manager, consent mode) Define and maintain the marketing KPI dictionary and data model; steward the single source of truth. Define data pipelines between martech platforms and enterprise solutions (Salesforce, COGNOS, Databricks). Set QA/alerting SLAs, prioritise analytics backlog. Advise on experimentation, attribution and MMM, recommend budget reallocations based on evidence.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 
 Design and build the marketing data foundation from scratch
 
 , including tracking architecture, event schemas, identity strategy, and data flows across martech and enterprise platforms.
 </li>
 <li>
 Tagging and implementation: Deploy and audit events, conversions, and consent, server-side GTM evaluation, manage parameter standards and de-duplication rules
 </li>
 <li>
 Platform integrations: Build robust connectors/APIs for GA4, GMP (CM360/DV360/SA360), Meta and other platforms. Unify with Databricks, COGNOS and Salesforce
 </li>
 <li>
 Data engineering: Model clean tables/views, implement data quality checks and documentation
 </li>
 <li>
 Dashboards and reporting: Deliver looker studio and Tableau dashboards, automate recurring reporting, provide training to channel owners
 </li>
 <li>
 Attribution and MMM: Deploy open source MMM (Meta Robyn, Google Meridian), design holdouts, support hybrid attribution and incrementality studies
 </li>
 <li>
 Governance and compliance: Ensure GDPR/Consent compliance, maintain audit trails, partner with legal on risk mitigation
 </li>
 <li>
 Troubleshooting and enablement: Act as a single point of contact for data/tracking issues, triage quickly, run enablement sessions and documentation
 </li>
 </ul>
 
 
 
 
 
 Key KPIs
 
 
 <ul>
 <li>
 Tag coverage rate and accuracy; reduced data discrepancy between platforms and data sources
 </li>
 <li>
 Pipeline uptime and latency SLAs; time to lag and time to insight reductions
 </li>
 <li>
 Dashboard adoption and stakeholder satisfaction
 </li>
 <li>
 Evidence based budget reallocation % driven by MMM/holdouts; lift from incrementality tests
 </li>
 <li>
 Compliance readiness; consent coverage, audit trail completeness
 </li>
 <li>
 Profile and Experience:
 </li>
 </ul>
 
 
 
 
 
 Educational Background:
 
 
 <ul>
 <li>
 Degree in Computer Science, Analytics or Data Science
 </li>
 </ul>
 
 
 
 
 
 Professional Experience:
 
 
 <ul>
 <li>
 5-8 years in analytics/data engineering or marketing analytics engineering roles
 </li>
 <li>
 Expertise in GTM/GA4/GMP/Meta tracking; strong SQL, experience with BigQuery or equivalent
 </li>
 <li>
 Hands on APIs
 </li>
 <li>
 Proficiency with dashboarding (Looker studio/Tableau) and at least one scripting language (Python or R)
 </li>
 <li>
 MMM/Attribution exposure (Robyn, Meridian) and understanding of privacy frameworks (GDPR. Consent mode)
 </li>
 </ul>
 
 
 
 
 
 Skills and competencies
 
 
 <ul>
 <li>
 Structured problem solving, bias to automate and standardise
 </li>
 <li>
 Clear communicator who can translate between technical and commercial stakeholders
 </li>
 <li>
 Strong ownership and prioritisation; able to manage technical backlog and SLAs
 </li>
 <li>
 Documentation discipline; enablement mindset to upskill the wider team
 </li>
 </ul>
 
 
 
 
 
 Tools and stack
 
 
 <ul>
 <li>
 BigQuery, Python/R, GA4, CM360/DV360/SA360, Meta
 </li>
 <li>
 Looker Studio/Tableau, Serverside GTM, privacy and consent platforms
 </li>
 <li>
 Salesforce, COGNOS, Databricks
 </li>
 </ul>
 
 
 
 
 
 Hertz is an equal opportunity employer, all applicants must have the legal right to work in the UK (Valid Passport / Relevant Visa).
 
 
 
 
 
 
 
 What You&rsquo;ll Get:
 
 
 <ul>
 <li>
 Up to 40% off any standard Hertz Rental in a Corporate country
 </li>
 <li>
 Paid Time Off
 </li>
 <li>
 Employee Assistance Programme for employees and family
 </li>
 </ul>
 
 
</div>

easyJet

<div>
 
 Luton/Hybrid
 
 
 
 
 Company
 
 
 
 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.
 
 
 
 Job Purpose
 
 
 
 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
 
 .
 
 
 
 
 Job Accountabilities
 
 
 
 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:
 
 
 <ul>
 <li>
 Define and drive the future direction of data engineering and analytics practices, ensuring alignment with business goals and technological advancements.
 </li>
 <li>
 Design and implement sophisticated data pipelines and transformations, delivering curated, high-quality datasets for advanced analytics, reporting, and AI/ML applications.
 </li>
 <li>
 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.
 </li>
 <li>
 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.
 </li>
 <li>
 Leads collaboration with BI Analysts and Data Scientists to refine methodologies, enhance reporting, and deliver scalable, production-ready feature engineering code.
 </li>
 <li>
 Drives engagement with business stakeholders, effectively communicating complex technical concepts in a clear, accessible manner to align analytics engineering initiatives with strategic goals.
 
 
 
 </li>
 </ul>
 
 Key Skills Required
 
 
 
 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
 
 :
 
 
 
 <ul>
 <li>
 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.
 </li>
 <li>
 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.
 </li>
 <li>
 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.
 </li>
 <li>
 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.
 </li>
 <li>
 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.
 </li>
 <li>
 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.
 
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Get In Return
 
 
 
 <ul>
 <li>
 Competitive base salary
 </li>
 <li>
 Up to 20% bonus
 </li>
 <li>
 25 days holiday
 </li>
 <li>
 BAYE, SAYE &amp; Performance share schemes
 </li>
 <li>
 7% pension
 </li>
 <li>
 Life Insurance
 </li>
 <li>
 Work Away Scheme
 </li>
 <li>
 Flexible benefits package
 </li>
 <li>
 Excellent staff travel benefits
 
 
 
 </li>
 </ul>
 
 About EasyJet
 
 
 
 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.
 
 
 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.
 
 
 
 Apply
 
 
 
 Complete your application on our careers site.
 
 
 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.
 
 
 
 Business Area
 
 
 
 Information Technology (IT)
 
 
 
 Primary Location
 
 
 
 United Kingdom-London-London Luton Airport
 
 
 
 Organisation
 
 
 
 Information Technology (IT)
 
 
 
 Schedule
 
 
 
 Full-time
 
 
 
 Unposting Date
 
 
 
 Ongoing
</div>

Senior Data Analytics Engineer

Deloitte

<div><div><div><div><div><div><div><div>Data Analytics Engineer &ndash; Software Engineer II
Role Overview: We are seeking a proactive and solutions-oriented Data Analyst 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.
Work you will do<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>
Key Responsibilities:
Outcome-Driven Accountability: 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.
Technical Leadership and Advocacy: 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.
Engineering Craftsmanship: 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.
Customer-Centric Engineering: 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;.
Incremental and Iterative Delivery: 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.
Cross-Functional Collaboration and Integration: 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;
Advanced Technical Proficiency: 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.
Domain Expertise: 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.
Effective Communication and Influence: Aligns with: Excellent communication skills, presenting complex ideas to varying audiences (technical/non-technical), and contributing to team and stakeholder discussions.
Engagement and Collaborative Co-Creation: 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.
The team: 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.
Key Qualifications:<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>
Good to have skills:
<div><ul><li>Experience with cloud analytics (AWS, Azure, GCP)</li></ul>
</div>2. Knowledge on BI tools like Tableau, SAP BOE is preferred<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>How You will Grow:<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> 

</div><div><div><div>Our purpose</div> 
<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>Our people and culture</div> 
<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>Professional development</div> 
<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>Benefits to help you thrive 
</div><div>
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</div></div></div></div></div></div><div><div><div>Requisition code: 357466</div></div></div></div>

Data Analytics Engineer - Software Engineer II

LimeFlight

<div>Join our fully remote, mission-driven team dedicated to pioneering sustainable inflight service management. Work on innovative technology solutions with global impact, collaborate within a diverse, international environment, and continuously enhance your skills through ongoing learning opportunities.
Headquartered in Zurich, Switzerland with team members across 11 countries, we offer a dynamic and engaging company culture that celebrates creativity, collaboration, and inclusion.
<h4 class="jobSectionHeader">About the role</h4>
We are hiring a Senior Data &amp; Analytics Engineer to take end-to-end ownership of our data platform and BI layer.
We are on a mission to contribute to a zero-waste future by drastically reducing food waste, fuel consumption, costs, and most importantly, CO₂ emissions in the airline industry. Every role in our company is a direct contributor to this vision - and as a Senior Data &amp; Analytics Engineer you will be at the forefront of turning data into meaningful insights, empowering our customers to effectively use them and drive real impact.
You will evolve a vendor-built BI solution into a modern, product-grade data platform and ensure that data is transformed into scalable, trusted, and actionable insights for both our customers and internal teams. You&rsquo;re not just building dashboards, you&rsquo;re enabling better decisions and measurable impact.
This role combines:<ul><li>
Data Engineering (pipelines, processing, customer facing exports, platform)</li><li>
Analytics Engineering (modeling, KPIs, semantic layer)</li><li>
Data Product Ownership (customer impact, insight generation)</li></ul><h4 class="jobSectionHeader">
What You&rsquo;ll Own</h4>
Platform, Architecture &amp; Pipelines
Own the end-to-end data platform (Databricks and Microsoft Fabric)<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>
Data Modeling &amp; Semantic Layer<ul><li>
Own Power BI 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>
Customer-Facing Analytics<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>
Data as Product<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>
Platform Quality, Operations, Security &amp; Governance<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>
Migration &amp; Insourcing (Initial Focus)<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">
What We&rsquo;re Looking For</h4>
Experience<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>
Technical &amp; Platform Skills<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>
Engineering Practices<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>
Nice-to-have<ul><li>
Azure infrastructure knowledge (IAM, networking)</li><li>
Data quality/testing frameworks (e.g., Great Expectations)</li></ul>
Mindset<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">
Language</h4>
Min. English C1<h4 class="jobSectionHeader">
Expected travel needs</h4>
2 annual one-week team events<h4 class="jobSectionHeader">
Our Tech Stack</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">
Hiring Process</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> 
LimeFlight is proud to be an equal opportunity employer.
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.
Join us and be part of a team committed to shaping a zero-waste future for aviation, where your ideas and passion truly matter.
Let&rsquo;s talk!</div>

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

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