data engineer

principal ai engineer

ai / ml engineer

ai automation engineer

ai engineer - remote

azure data engineer

Coca-Cola HBC

<div>
 
 
 Department:
 
 Data Insights &amp; Automation, Digital &amp; Technology Platform Services.
 
 
 
 Location:
 
 Cairo, Egypt.
 
 
 
 
 
 We are looking for a highly skilled and experienced
 
 Azure Data Engineer
 
 with significant technical skills in Azure and strong business acumen to join our team in Coca-Cola Hellenic Digital &amp; Technology Platform Services (DTPS) and be part of the Data Platforms team. You will have the opportunity to contribute to the strategy, design and development of our Enterprise and Operational Reporting, providing insights and supporting decision making for end users.
 
 
 The role involves significant collaboration with business and IT teams, opportunity to integrate and transform data from various data systems into structures that are suitable for building analytical solutions, design, develop and implement Azure-based solutions connecting certified and validated data sources to Power BI front-end visualizations - creating a single source of truth for reporting across CCH.
 
 
 
 
 
 
 YOUR KEY RESPONSIBILITIES:
 
 
 
 &bull; Design, build, and maintain scalable ELT/ETL pipelines using Azure Data Factory, ensuring reliability and performance at terabyte scale.
 
 
 &bull; Contribute to end-to-end pipeline health: monitoring, alerting, incident response, and continuous improvement.
 
 
 &bull; Identify and resolve bottlenecks across ingestion, transformation, and serving layers; drive measurable performance gains.
 
 
 &bull; Implement and extend existing medallion architecture patterns.
 
 
 &bull; Develop data ingestion processes from multiple sources, ensuring accuracy, completeness, and consistency.
 
 
 &bull; Support the migration from SAP BW, ensuring data continuity and quality throughout.
 
 
 &bull; Ensure data integrity and availability through appropriate storage solutions, partitioning strategies, and access controls.
 
 
 &bull; Work independently on clearly scoped tasks, communicating progress and blockers regularly with your team.
 
 
 &bull; Collaborate with data scientists, BI analysts, and business stakeholders to understand requirements and translate them into technical solutions.
 
 
 &bull; Participate in agile ceremonies, contribute to sprint planning, and own your backlog items end-to-end.
 
 
 
 
 
 
 ARE THESE YOUR SECRET INGREDIENTS?
 
 
 
 &bull; Bachelor's degree in Information Technology, Computer Science, or related field.
 
 
 &bull; 3+ years of experience in data engineering with hands-on exposure to Azure (Azure Data Factory, Azure Data Lake Storage, Fabric).
 
 
 &bull; Proven experience designing and building production-grade data pipelines that handle large volumes of data reliably.
 
 
 &bull; Strong SQL skills and experience with data modelling, schema design, and query optimization.
 
 
 &bull; Hands-on experience with Databricks (PySpark / Spark SQL) for large-scale data transformation.
 
 
 &bull; Working proficiency in Python; exposure to Scala or C#/.NET is a plus.
 
 
 &bull; Understanding of data warehouse and lakehouse concepts.
 
 
 &bull; Ability to manage your own tasks within a defined sprint scope and deliver consistently.
 
 
 &bull; Good communication skills - able to translate technical concepts for business stakeholders and vice versa.
 
 
 &bull; Excellent problem-solving and debugging skills.
 
 
 &bull; Excellent spoken and written English
 
 
 &bull; Communication, organizational and analytical skills
 
 
 
 Preferred Qualifications:
 
 
 
 &bull; Exposure to real-time or near-real-time streaming concepts (Azure Event Hubs, Apache Kafka, or Spark Streaming).
 
 
 &bull; Basic experience with CI/CD practices, Git version control, and familiarity with Azure DevOps.
 
 
 &bull; Familiarity with infrastructure-as-code concepts (Terraform) is a bonus.
 
 
 &bull; Awareness of SAP BW data structures and export mechanisms; prior migration experience is not expected.
 
 
 &bull; Some exposure to big data technologies such as Hadoop, Spark, or Hive.
 
 
 &bull; Curious, problem-solving mindset - comfortable digging into issues with support from senior teammates.
 
 
 &bull; Exposure to Power BI or DAX for understanding how data is consumed downstream.
 
 
 
 
 
 
 ABOUT YOUR NEW TEAM:
 
 
 
 We are Coca-Cola Hellenic, a growth-focused consumer goods business and strategic bottling partner of the Coca-Cola Company. We bottle, distribute and sell an unrivalled range of products in 29 markets in Europe, Africa and Eurasia. As we do, we create value for all stakeholders, support socio-economic growth and build a more positive environmental impact.
 
 
 We bring together more than 30,000 people from over 70 nationalities, coming from five continents. The diversity of our markets, from mature to emerging economies, provides a wide range of attractive opportunities for growth.
 
 
 We nurture our talents. We give opportunities to people across all functions and levels, as well as different geographies, backgrounds and education. We are willing to take a risk on the people we believe in, even if they don&rsquo;t have the perfect experience. We have faith in what every person can be.
 
 
 And although we have so much to be proud of, we always stay humble. We believe the real magic happens &ndash; for us and for you &ndash; when we OPEN UP.
 
 
 
 
 
 
 AT COCA-COLA HBC, DIVERSITY HELPS US THRIVE
 
 
 
 At Coca-Cola HBC, we are an inclusive employer that thrives on diversity. This means our environment provides equal opportunities for all, regardless of race, color, religion, age, disability, sexual orientation, or gender identity. Join us in nurturing a culture where everyone belongs and contributes to our collective success.
 
</div>

Azure Data Engineer

Sana Commerce

<div>
 
 What started in 2007 with a pizza and a plan has grown into a fast-moving SaaS company empowering manufacturers, distributors, and wholesalers to thrive in complex B2B commerce.
 
 
 
 
 Our mission is simple: help businesses build stronger relationships through seamless digital commerce.
 
 
 
 
 At Sana Commerce, you&rsquo;ll join a team that&rsquo;s bold, growth-oriented, and customer-obsessed, where every engineer has real ownership and impact.
 
 
 
 
 We are looking for a
 
 Senior Data Engineer
 
 to design, build, and optimize our
 
 Azure and Databricks-based data infrastructure
 
 . You will play a critical role in developing scalable
 
 ETL pipelines, data ingestion frameworks, and
 
 
 contribute to
 
 
 AI/ML-powered solutions
 
 that drive internal decision-making and customer-facing insights.
 
 
 
 
 This is a hands-on role that requires expertise in
 
 Azure Data Services, Databricks, and Python/SQL
 
 . You will work closely with
 
 Data Architects, Engineers, and Product teams
 
 to develop robust data solutions that power
 
 analytics, personalization, and AI-driven customer experiences
 
 .
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 Data Pipeline Development &amp; Infrastructure
 
 
 
 
 <ul>
 <li>
 Design, build, and maintain
 
 scalable data pipelines
 
 </li>
 <li>
 Develop
 
 real-time and batch data processing
 
 frameworks for structured and unstructured data.
 </li>
 <li>
 Implement
 
 ETL/ELT workflows
 
 to ingest data from various sources, ensuring
 
 high availability and performance
 
 .
 </li>
 <li>
 Optimize
 
 data storage and retrieval
 
 of data in (near) real time and batch processes
 </li>
 <li>
 Ensure
 
 cost-efficient
 
 and
 
 high-performance
 
 data infrastructure that scales with business needs.
 </li>
 </ul>
 
 
 Data Solutions &amp; AI-Driven Applications
 
 
 
 
 <ul>
 <li>
 develop data pipelines for
 
 ML recommenders, search functionality, and AI-enhanced features
 
 .
 </li>
 <li>
 Develop and maintain
 
 data models, APIs, and integrations
 
 to support analytics and customer applications.
 </li>
 <li>
 Support
 
 eCommerce-related data solutions
 
 , including product recommendations, customer segmentation, and personalization models.
 </li>
 </ul>
 
 
 Collaboration &amp; Continuous Improvement
 
 
 
 
 <ul>
 <li>
 Work closely with
 
 Data Architects, Analysts, and Product Teams
 
 to understand data requirements and deliver best-in-class solutions.
 </li>
 <li>
 Monitor and troubleshoot
 
 performance issues
 
 , ensuring high availability and efficiency of data pipelines.
 </li>
 <li>
 Continuously optimize
 
 cost, performance, and scalability
 
 of data engineering solutions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 6+ years of experience as a
 
 Data Engineer
 
 , working with
 
 Azure and Databricks
 
 </li>
 <li>
 Strong expertise in
 
 data pipeline development, ETL workflows, and real-time/batch data processing
 
 .
 </li>
 <li>
 Experience in
 
 big data technologies, and large-scale data storage
 
 .
 </li>
 <li>
 Familiarity with
 
 data governance, security, and compliance best practices
 
 and
 
 tools
 
 </li>
 <li>
 Proficiency in
 
 Python,
 
 
 and
 
 
 SQL,
 
 for data transformation, data quality and automation.
 </li>
 <li>
 Strong experience in
 
 optimizing data performance and cost-efficiency in cloud environments
 
 .
 </li>
 </ul>
 
 
 Nice to Have
 
 
 
 
 <ul>
 <li>
 Experience with
 
 eCommerce data solutions
 
 , such as customer segmentation, recommendation engines, and personalization models.
 </li>
 <li>
 Knowledge of
 
 event-driven architectures, streaming data processing, and real-time analytics
 
 .
 </li>
 <li>
 Familiarity with
 
 LLM-based AI applications and OpenAI
 
 
 or similar
 
 
 APIs
 
 .
 </li>
 </ul>
 
 
 Why you&rsquo;ll love working here
 
 
 
 
 <ul>
 <li>
 Impact from day one &ndash; Join a scale-up where your ideas shape how global businesses operate online.
 </li>
 <li>
 Continuous learning &ndash; Access a structured onboarding rated 9.1/10 by previous hires, mentorship, and feedback culture.
 </li>
 <li>
 Hybrid flexibility &ndash; Work from our office in Alexandria 3 days per week and from home 2 days.
 </li>
 <li>
 Career growth &ndash; Expand your technical and leadership scope in a company built for long-term success.
 </li>
 </ul>
 
 
 Our values
 
 
 
 
 
 At Sana Commerce, our values drive everything we do:
 
 
 
 <ul>
 <li>
 Champions of Our League &ndash;
 
 We deliver lasting success, balancing quick wins and long-term value
 
 </li>
 <li>
 Supercharge Our Customers &ndash;
 
 We&rsquo;re revolutionizing B2B commerce together, helping our customers to lead and succeed.
 
 </li>
 <li>
 Determined to Grow &ndash;
 
 We embrace challenges, growing and raising the bar for ourselves and our industry.
 
 </li>
 <li>
 Bold Together &ndash;
 
 We dare to be bold because we have each other&rsquo;s back.
 
 </li>
 </ul>
 
 
 Ready to build reliability that scales?
 
 
 
 
 
 Apply now and help shape the foundation of our next-generation SaaS platform.
 
 
 
 
 
 
 Additional Information
 
 
 
 
 
 
 
 
 
 
 
</div>

Senior Data Engineer - Alexandria

Datamatics Technologies

<div>
 Job Description: AI / ML Engineer
 
 
 Job Title:
 
 AI / ML Engineer
 
 
 Experience:
 
 3&ndash;11 Years
 
 
 Location:
 
 &nbsp;
 
 
 Riyadh (Onsite)
 
 
 
 
 Employment Type:
 
 Full-Time
 
 Job Overview
 
 We are seeking a skilled
 
 AI / ML Engineer
 
 with
 
 3&ndash;11 years of experience
 
 to design, develop, deploy, and optimize machine learning and generative AI solutions. The ideal candidate will have hands-on expertise in building scalable AI/ML models, working with cloud-native AI platforms, and implementing production-ready machine learning pipelines. Experience with modern AI frameworks, large language models (LLMs), and MLOps practices is highly desirable.
 
 Key Responsibilities
 <ul>
 <li>
 Design, develop, train, and deploy machine learning and deep learning models for enterprise applications
 </li>
 <li>
 Build and optimize end-to-end ML pipelines for data ingestion, model training, evaluation, and deployment
 </li>
 <li>
 Develop Generative AI and LLM-powered applications using modern AI frameworks
 </li>
 <li>
 Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions
 </li>
 <li>
 Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security
 </li>
 <li>
 Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation
 </li>
 <li>
 Implement MLOps best practices including model versioning, monitoring, and CI/CD automation
 </li>
 <li>
 Stay current with advancements in AI, machine learning, and cloud AI services
 </li>
 </ul>
 Required Technical SkillsCloud AI Platforms
 <ul>
 <li>
 Hands-on experience with
 
 GCP Vertex AI or Azure Machine Learning or AWS SageMaker
 
 </li>
 <li>
 Experience with
 
 Azure OpenAI or AWS Bedrock
 
 for Generative AI solutions
 </li>
 <li>
 Experience with
 
 BigQuery ML and Dataflow
 
 for data processing and machine learning workflows
 </li>
 </ul>
 Programming &amp; Machine Learning
 <ul>
 <li>
 Strong proficiency in
 
 Python
 
 </li>
 <li>
 Experience developing machine learning solutions using
 
 TensorFlow or PyTorch
 
 </li>
 <li>
 Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts
 </li>
 </ul>
 Generative AI &amp; LLM Frameworks
 <ul>
 <li>
 Experience with
 
 Hugging Face and LangChain
 
 for building LLM-powered applications
 </li>
 <li>
 Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases is preferred
 </li>
 </ul>
 Data Engineering &amp; Analytics
 <ul>
 <li>
 Experience with
 
 Databricks
 
 for data engineering, model development, and analytics workflows
 </li>
 <li>
 Strong understanding of data preprocessing, feature engineering, and large-scale data processing
 </li>
 </ul>
 MLOps &amp; Deployment
 <ul>
 <li>
 Experience deploying machine learning models into production
 </li>
 <li>
 Knowledge of Docker, Kubernetes, CI/CD pipelines, and model monitoring is an advantage
 </li>
 </ul>
 Qualifications
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field
 </li>
 <li>
 
 3&ndash;11 years
 
 of professional experience in AI, Machine Learning, or Data Science
 </li>
 <li>
 Strong analytical, mathematical, and problem-solving skills
 </li>
 <li>
 Experience working in Agile development environments
 </li>
 <li>
 Excellent communication and collaboration skills
 </li>
 </ul>
 Preferred Skills
 <ul>
 <li>
 Experience with Large Language Models (LLMs) and Generative AI applications
 </li>
 <li>
 Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents
 </li>
 <li>
 Experience with distributed model training and cloud-native AI architectures
 </li>
 <li>
 Cloud certifications in AWS, Azure, or Google Cloud are a plus
 </li>
 </ul>
 Key Technology Stack
 <ul>
 <li>
 
 Cloud AI:
 
 
 GCP Vertex AI or Azure Machine Learning or AWS SageMaker
 
 </li>
 <li>
 
 Generative AI:
 
 
 Azure OpenAI or AWS Bedrock
 
 
 and
 
 Large Language Models (LLMs)
 </li>
 <li>
 
 Data Processing:
 
 
 BigQuery ML and Dataflow
 
 
 and
 
 Databricks
 </li>
 <li>
 
 Programming:
 
 Python
 </li>
 <li>
 
 Machine Learning Frameworks:
 
 
 TensorFlow or PyTorch
 
 </li>
 <li>
 
 LLM Frameworks:
 
 
 Hugging Face or LangChain
 
 </li>
 <li>
 
 MLOps:
 
 Docker
 
 and
 
 Kubernetes
 
 and
 
 CI/CD (Preferred)
 </li>
 </ul>
</div>

AI / ML Engineer

Whitehall Resources

<div>
 
 
 
 Senior IoT Solutions Engineer
 
 
 
 
 An exciting new
 
 Senior IoT Solutions Engineer
 
 opportunity has arisen, working for a leading organisation investing in the next generation of connected products and smart technology solutions.
 
 
 In this role, you will play a key part in designing, developing and supporting scalable IoT platforms. You'll work across the full IoT lifecycle, helping to deliver innovative connected solutions used in commercial environments.
 
 
 If you are an experienced IoT Engineer with strong cloud, integration and data platform expertise, we would love to hear from you!
 
 
 
 
 Do you have:
 
 
 
 <ul>
 <li>
 5+ years' experience designing and delivering enterprise IoT solutions
 </li>
 <li>
 Strong experience with IoT platforms, and cloud-based architectures
 </li>
 <li>
 Experience with Azure IoT or similar cloud IoT platforms
 </li>
 <li>
 Hands-on experience with REST APIs, MQTT, Kafka and event-driven integration patterns
 </li>
 <li>
 Experience working with SQL databases
 </li>
 <li>
 Deep understanding of commercial IoT use cases
 </li>
 <li>
 Experience integrating IoT platforms with enterprise applications, data platforms and analytics solutions
 </li>
 <li>
 Excellent problem-solving skills with experience troubleshooting connectivity and performance issues
 </li>
 </ul>
 
 
 
 Do you want:
 
 
 
 <ul>
 <li>
 To play a key role in the design and evolution of enterprise IoT platforms?
 </li>
 <li>
 To work with modern cloud, data and integration technologies?
 </li>
 <li>
 To collaborate with international engineering, data and product teams?
 </li>
 <li>
 To be part of exciting projects delivering connected products at scale?
 </li>
 </ul>
 
 
 If so, then please do apply!
 
 
 
 
 IoT | Azure | MQTT | Kafka | REST API | Event-Driven Architecture | Cloud Integration | SQL | Python | JavaScript | Node.js
 
 
</div>

Senior IoT Solutions Engineer

Integrant, Inc.

<div>
 
 We're on the lookout for exceptional individuals to join our team as
 
 Principal Data Engineers
 
 . As a part of our team, you'll be driving change and making a significant impact in the gaming industry.
 
 <ul>
 <li>
 Lead the design, development, and maintenance of end-to-end data analytical solutions using Microsoft on-premises and cloud technologies.
 </li>
 <li>
 Engage in collaborative requirement elicitation activities with our valued clientele.
 </li>
 <li>
 Mentor and guide junior team members in the field of data engineering.
 </li>
 <li>
 Showcase your expertise by delivering innovative analytical solutions to our clients and contributing to knowledge transfer within the organization.
 </li>
 
 </ul>
 
 Requirements
 
 
 <ul>
 <li>
 6+ years of experience as a data engineer.
 </li>
 <li>
 Familiarity with analytical architectures including Data Warehouses, Data Lakes and Data Lakehouses.
 </li>
 <li>
 Knowledge of Microsoft relational engines available - both on-premises (MS SQL Server) and on the cloud (Azure SQL, Azure Synapse Analytics Dedicated Pools).
 </li>
 <li>
 Knowledge of query and workload optimization.
 </li>
 <li>
 Knowledge of administrating and managing analytical solutions both on premises and on the cloud.
 </li>
 <li>
 Knowledge of NoSQL offerings on Azure (e.g. CosmosDB).
 </li>
 <li>
 Knowledge of setting up Data Lakes on ADLS gen 2 and Azure Synapse Analytics.
 </li>
 <li>
 Knowledge of using SSIS and Azure Data Factory to set up ETL jobs.
 </li>
 <li>
 Knowledge of setting up OLAP solutions using SSAS.
 </li>
 <li>
 Familiarity with Azure Data Catalog to manage data lake metadata.
 </li>
 <li>
 Knowledge of governance over Azure based analytical solutions including using tools such as Purview, Active Directory, Key Vault, Azure DevOps, etc.
 </li>
 <li>
 Knowledge of using Azure Stream Analytics to capture and analyze data in real time.
 </li>
 <li>
 Knowledge of setting up data warehouse solutions both on-premises (using MS SQL Server) and on the cloud (using Azure Synapse Analytics).
 </li>
 <li>
 Knowledge of Dimensional Modeling (Dimensions, Facts, Slowly Changing Dimensions, Outriggers, Role Playing Dimensions, Junk Dimensions, Degenerate Dimensions, Multi-valued Dimensions, Transactional Facts, Periodic Snapshot Facts and Accumulating Snapshot Facts).
 </li>
 <li>
 Knowledge of implementing common ETL patterns to support data warehouse workloads.
 </li>
 <li>
 Knowledge of using U-SQL, PolyBase and Azure Data Lake Analytics to perform federated querying.
 </li>
 <li>
 Knowledge of PowerBI.
 </li>
 <li>
 Familiarity with SSRS.
 </li>
 <li>
 
 Snowflake Experience:
 
 Experience with Snowflake is required.
 </li>
 </ul>
 
 Nice to Have:
 
 <ul>
 <li>
 An MSc in Computer Science or other relevant field.
 </li>
 <li>
 Familiarity with Azure Databricks.
 </li>
 <li>
 Familiarity with DataOps
 </li>
 <li>
 Familiarity with Azure Cognitive Services.
 </li>
 <li>
 Familiarity with Azure ML.
 </li>
 <li>
 Familiarity with MLOps.
 </li>
 <li>
 Familiarity of containerization tools and frameworks (Docker, Kubernetes, etc.)
 </li>
 <li>
 Familiarity with Azure HD Insight.
 </li>
 <li>
 Familiarity with the Hadoop ecosystems, including tools like Hive, Spark and Kafka.
 </li>
 <li>
 Familiarity with Azure Functions to perform lightweight transformations.
 
 </li>
 </ul>
 
 Benefits
 
 
 <ul>
 <li>
 Salary paid in USD
 </li>
 <li>
 Six-month career advancing opportunities
 </li>
 <li>
 Supportive and friendly work environment
 </li>
 <li>
 Premium medical insurance [employee +family]
 </li>
 <li>
 English language development courses
 </li>
 <li>
 Interest-free loans paid over 2.5 years
 </li>
 <li>
 Technical development courses
 </li>
 <li>
 Planned overtime program (POP)
 </li>
 <li>
 Employment referral program
 </li>
 <li>
 Premium location in Maadi
 </li>
 <li>
 Social insurance
 </li>
 </ul>
</div>

Principal Data Engineer

<div>
 Job Description: Data Science &amp; Analytics Engineer
 
 
 Job Title:
 
 Data Science &amp; Analytics Engineer
 
 
 Experience:
 
 3&ndash;11 Years
 
 
 Location:
 
 
 
 Riyadh - Onsite
 
 
 
 
 Employment Type:
 
 Full-Time
 
 Job Overview
 
 We are looking for a talented
 
 Data Science &amp; Analytics Engineer
 
 with
 
 3&ndash;11 years of experience
 
 to transform complex data into actionable business insights. The ideal candidate will have expertise in data science, statistical analysis, predictive modeling, data visualization, and modern analytics platforms. You will work closely with business stakeholders, data engineers, and technology teams to develop data-driven solutions that support strategic decision-making.
 
 Key Responsibilities
 <ul>
 <li>
 Design, develop, and deploy predictive and analytical models to solve business problems
 </li>
 <li>
 Perform data exploration, statistical analysis, feature engineering, and model evaluation
 </li>
 <li>
 Build interactive dashboards, reports, and visualizations for business stakeholders
 </li>
 <li>
 Develop scalable data analytics solutions using modern cloud and big data platforms
 </li>
 <li>
 Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions
 </li>
 <li>
 Analyze structured and unstructured datasets to identify trends, patterns, and opportunities
 </li>
 <li>
 Ensure data quality, governance, and best practices across analytics initiatives
 </li>
 <li>
 Present analytical findings and recommendations to technical and non-technical audiences
 </li>
 <li>
 Continuously improve analytics processes, reporting capabilities, and model performance
 </li>
 </ul>
 Required Technical SkillsProgramming &amp; Data Science
 <ul>
 <li>
 Strong proficiency in
 
 Python or R
 
 for data analysis, statistical modeling, and machine learning
 </li>
 <li>
 Experience with data manipulation, exploratory data analysis (EDA), and predictive analytics
 </li>
 </ul>
 Data Science Platforms
 <ul>
 <li>
 Hands-on experience with
 
 Databricks or Dataiku
 
 for data science, machine learning, and collaborative analytics
 </li>
 <li>
 Experience developing end-to-end analytical workflows and model deployment
 </li>
 </ul>
 Business Intelligence &amp; Visualization
 <ul>
 <li>
 Strong experience with
 
 Power BI or Tableau or Looker
 
 for dashboard development and data visualization
 </li>
 <li>
 Ability to create interactive reports and executive-level dashboards
 </li>
 </ul>
 Data Warehousing &amp; Analytics
 <ul>
 <li>
 Experience with
 
 BigQuery or Snowflake
 
 for large-scale analytics and data warehousing
 </li>
 <li>
 Strong understanding of SQL, data modeling, and analytical query optimization
 </li>
 </ul>
 Analytics &amp; Machine Learning
 <ul>
 <li>
 Experience with statistical analysis, forecasting, classification, clustering, and regression models
 </li>
 <li>
 Familiarity with machine learning libraries and model evaluation techniques
 </li>
 </ul>
 Qualifications
 <ul>
 <li>
 Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Information Technology, or a related field
 </li>
 <li>
 
 3&ndash;11 years
 
 of professional experience in Data Science, Business Analytics, or Advanced Analytics
 </li>
 <li>
 Strong analytical, mathematical, and problem-solving skills
 </li>
 <li>
 Excellent communication and presentation skills
 </li>
 <li>
 Experience working in Agile/Scrum environments
 </li>
 </ul>
 Preferred Skills
 <ul>
 <li>
 Experience with cloud analytics platforms on AWS, Microsoft Azure, or Google Cloud Platform
 </li>
 <li>
 Knowledge of MLOps, model deployment, and AI-driven analytics
 </li>
 <li>
 Experience with ETL/ELT processes and data engineering concepts
 </li>
 <li>
 Familiarity with Generative AI, Large Language Models (LLMs), or AI-assisted analytics is an advantage
 </li>
 <li>
 Relevant certifications in Data Science, Analytics, or Cloud technologies are a plus
 </li>
 </ul>
 Key Technology Stack
 <ul>
 <li>
 
 Programming Languages:
 
 
 Python or R
 
 </li>
 <li>
 
 Data Science Platforms:
 
 
 Databricks or Dataiku
 
 </li>
 <li>
 
 Business Intelligence:
 
 
 Power BI or Tableau or Looker
 
 </li>
 <li>
 
 Data Warehouse:
 
 
 BigQuery or Snowflake
 
 </li>
 <li>
 
 Analytics:
 
 Statistical Analysis
 
 and
 
 Predictive Modeling
 
 and
 
 Machine Learning
 
 and
 
 Data Visualization
 </li>
 <li>
 
 Cloud Platforms:
 
 
 AWS or Microsoft Azure or Google Cloud Platform
 
 (Preferred)
 </li>
 </ul>
</div>

Data Science & Analytics Engineer

Henkel

<div>
 
 About this Position
 
 The Data Engineer supports the development and operation of Henkel&rsquo;s enterprise metadata platform, DataHub. The role focuses on building scalable data engineering and governance solutions that connect key enterprise platforms into one centralized ecosystem serving global data consumers.
 
 
 As part of a hands-on engineering environment, the position contributes to data quality, automation, and cloud-based capabilities that strengthen how data is discovered, understood, and trusted across Henkel.
 
 
 
 What You&acute;ll Do
 
 
 
 <ul>
 <li>
 Build and maintain scheduled metadata ingestion pipelines integrating platforms such as Databricks Unity Catalog, Power BI, SAP, and Azure Synapse into DataHub
 </li>
 <li>
 Support and enhance governance automation solutions covering dataset compliance, ownership, descriptions, lineage, and automated tagging
 </li>
 <li>
 Develop and improve data quality and completeness scoring capabilities across the enterprise data landscape
 </li>
 <li>
 Work directly with DataHub SDKs, REST APIs, and GraphQL APIs to support metadata operations and integrations
 </li>
 <li>
 Contribute to AI-enabled metadata access capabilities supporting intelligent assistants and modern AI solutions
 </li>
 <li>
 Build and maintain data lineage between source systems and downstream consumers
 </li>
 <li>
 Develop scalable cloud-native solutions running on Azure Kubernetes Service (AKS)
 </li>
 <li>
 Collaborate with global and cross-functional teams to support scalable and reliable enterprise data solutions
 </li>
 <li>
 Support engineering best practices including testing, monitoring, and continuous platform enhancements
 
 
 </li>
 </ul>
 
 What makes you a good fit
 
 
 
 <ul>
 <li>
 </li>
 <li>
 Strong experience with Python and SQL, including working with analytical databases such as PostgreSQL or Databricks
 </li>
 <li>
 Experience building and maintaining scalable and scheduled data pipelines, including automation, error handling, and reliability practices
 </li>
 <li>
 Understanding of REST APIs, GraphQL, and system integrations
 </li>
 <li>
 Experience with cloud platforms and services, preferably Microsoft Azure and Databricks
 </li>
 <li>
 Familiarity with containerization technologies and Kubernetes-based environments
 </li>
 <li>
 Experience with metadata platforms or data governance solutions such as DataHub or similar tools is considered a plus
 </li>
 <li>
 Familiarity with CI/CD pipelines, infrastructure automation, and modern engineering practices is an advantage
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills
 </li>
 <li>
 Ability to work independently and collaborate effectively with technical and non-technical stakeholders
 </li>
 <li>
 Passion for data quality, governance, automation, and scalable engineering solutions
 </li>
 <li>
 Comfortable working with modern technologies, open-source solutions, and continuously learning new concepts and tools
 
 
 </li>
 </ul>
 
 Some perks of joining Henkel
 
 
 
 <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>

Data Engineer

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