Senior Data Engineer – Data Platform & Analytics

About the role

The Senior Data Engineer will own the structural elements of data, including storage, pipelines and interfaces with analytics platforms. Working within the Data Center of Excellence, you will drive data requirements, modelling and testing for multiple use cases and define end‑to‑end data flows from ingestion to consumption.

Key responsibilities

• Collaborate across teams to design, build and maintain the Operations data mart (ETL, data modelling, metric design, reporting/dashboarding).
• Lead investigations of content usage and A/B testing streams.
• Promote and embed data‑engineering best practices throughout the team.
• Develop high‑quality software, document system requirements and create conceptual and detailed architectures.
• Provide technical guidance on data architecture and models to senior IT and business leaders.
• Define and implement data flows, ensuring data availability, quality and completeness for assigned use cases.
• Participate in data modelling, testing and extraction to solve analytical problems.
• Work closely with data scientists, software engineers and IT architects to maintain state‑of‑the‑art data quality.

Required profile

• 5+ years of experience in data engineering, business analytics or business intelligence.
• 3+ years of hands‑on work with stored procedures, CTEs, window functions and partitioning.
• Strong understanding of ETL concepts and workflows.
• Willingness to work across multiple platforms such as MSSQL, PostgreSQL, Hadoop and Linux.
• Experience with big‑data integration, HiveQL, MapReduce, REST APIs and tools like Denodo or Datameer.
• Deep knowledge of data‑lake/lakehouse architectures and data‑warehousing concepts.
• Advanced SQL skills, dimensional modelling and schema optimisation.
• Familiarity with data‑governance frameworks, metadata management and enterprise‑level security.

Required skills

• MSSQL
• PostgreSQL
• Hadoop
• Linux
• HiveQL
• MapReduce
• REST API
• Denodo
• Datameer
• Data lake architectures
• Lakehouse architectures
• Data warehousing
• Dimensional modelling
• Advanced SQL
• Stored procedures
• Common Table Expressions (CTE)
• Window functions
• Partitioning
• ETL concepts
• Big data integration
• Data governance frameworks
• Metadata management
• Encryption at rest
• Encryption in transit