We are seeking a Data Engineer to support end-to-end data delivery – from source-system analysis and data modeling through pipeline engineering and analytics enablement. Working within the target-state architecture, you will model data, build reliable end-to-end pipelines, and help turn complex datasets into trusted, decision-ready insight. The role combines hands-on data engineering with solid data modeling and architecture awareness and the analytical curiosity of a data analyst, operating across a multicultural, multinational environment with occasional travel to customer sites.
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Responsibilities
- Design and build scalable data pipelines (batch and real-time/streaming) from multiple data sources.
- Develop and maintain data models (conceptual, logical, physical; star/snowflake schemas).
- Work across modern data architectures (lake, warehouse, lakehouse) including ingestion, storage, and processing.
- Ensure data quality, integrity, and lineage through validation, monitoring, and observability.
- Optimize data processing for performance, scalability, and cost efficiency.
- Implement ETL/ELT workflows, orchestration, and automated data pipelines.
- Apply software engineering best practices (version control, testing, CI/CD).
- Collaborate with business and technical stakeholders to translate requirements into data solutions.
- Support data integration, cleansing, and migration from legacy systems.
- Maintain documentation, metadata, and adhere to data governance and security standards.
Qualifications
- Minimum 5 years of experience across data engineering, data modeling, and data analysis, with exposure to data architecture.
- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- Proven experience as a data analyst with strong knowledge of statistical methods and data visualization.
- Demonstrated experience delivering production-grade data pipelines and platforms.
- Mandatory: Hands-on experience with Microsoft Azure data stack (Azure Data Factory, Databricks/Synapse, ADLS Gen2, Azure SQL).
Technical Skills
- Advanced data querying and manipulation, including complex logic, analytical functions, and performance tuning.
- Proficiency in a data engineering/data analysis programming language.
- Hands-on experience across the full data model lifecycle using industry-standard modeling tools.
- Strong expertise defining granularity and identifying facts and dimensions for star and snowflake schemas based on business requirements.
- ETL/ELT design, data integration, workflow orchestration, and data-cleansing automation.
- Distributed processing and large-scale (big data) handling.
- Data warehousing and data lake/lakehouse storage architecture.
- Knowledge of statistics and experience using statistical methods to analyze datasets.
- Business intelligence and data visualization for self-service reporting.
- Cloud data platform experience across ingestion, storage, processing, and serving.
- Familiarity with version control, continuous integration and delivery, and data observability/quality practices.
