Senior Data Engineer
Posted
Summary
A Senior Data Engineer in Dublin who migrates, ingests, validates, and reconciles data feeding an insurance pricing data mart — cleaning and transforming raw source data and writing SQL and Python for pipelines, while helping shape the move to a new cloud data platform (e.g., Databricks, Snowflake, AWS, Azure).
The role of Senior Data Engineer involves extensive experience in data engineering, particularly in data migration, testing, validation, and reconciliation. The ideal candidate will possess a strong foundation in data engineering concepts and skills required for effective operation in relevant environments.
Main Responsibilities
Key responsibilities include:
- Define and document the requirements for the current pricing data mart as part of the application transformation.
- Ensure data is successfully fed back into the pricing data marts during and after the migration.
- Ingest data files into the Pricing Datamart.
- Validate incoming data upon delivery for completeness, accuracy, and conformance.
- Identify, investigate, and resolve data quality issues.
- Clean and transform raw source data to meet Pricing Datamart standards.
- Write, maintain, and optimize SQL and Python scripts to support workflows.
- Support the design and implementation of data pipelines and integrations.
- Contribute to the longer-term strategy for migrating the Pricing team to a new target data platform.
- Work with technical teams on data architecture decisions.
Responsibilities
Key Requirements
- Strong understanding of data engineering concepts, including data pipelines, data marts, ETL/ELT processes, and data warehousing.
- Experience working with SQL and Python for data ingestion, transformation, and validation.
- Strong analytical and problem-solving skills.
- Ability to manage competing priorities effectively.
- Experience with cloud-based data services and platforms.
Nice to Have
- Experience in the insurance or health insurance sector.
- Experience in Pricing and Underwriting departments.
- Familiarity with modern data platforms (e.g., "Databricks, Snowflake, AWS, Azure or similar").
- Experience with project management methodologies (Agile, Waterfall or hybrid).
- Knowledge of data governance frameworks and data quality management.
- Experience with application migration or platform consolidation programmes.