Senior Data Engineer

Major responsibilities:
- Design, build, and maintain data infrastructure for large-scale data processing, analytics, and reporting.
- Create and maintain dimensional data models, including star schemas and snowflake schemas, to support efficient querying.
- Build, maintain, and optimize ETL pipelines, integrating data from multiple sources.
- Optimize queries, indexes, storage, and other components of the data pipeline to improve performance and efficiency.
- Implement data quality checks to ensure data accuracy, completeness, and consistency
- Develop validation frameworks to detect data anomalies and discrepancies.
- Translate business requirements into technical solutions in collaboration with business analysts and other technical teams.
- Maintain documentation of data flows, schemas, and processes to support transparency and knowledge sharing.
- Implement access controls and data masking where required.
- Ensure data engineering solutions comply with data governance policies and applicable regulatory requirements.
We'd love to hear from you if you have:
- 5+ years of experience in data engineering, including 2–3 years working with Azure.
- Strong SQL skills, including complex analytical queries, stored procedures, and performance optimization.
- Proficiency in Python/PySpark for large-scale data processing and ETL/ELT pipeline development.
- Hands-on experience with Azure Synapse Analytics, including Dedicated SQL Pool and Synapse Pipelines.
- Understanding of Medallion Architecture (Bronze, Silver, Gold) and experience building scalable data warehouses.
- Experience with dimensional data modeling, including star schemas, fact and dimension tables.
- Knowledge of data quality practices, including data cleaning, validation, and standardization.
- Experience preparing analytics-ready data for Power BI or other BI tools.
- English level B2 or higher.
Nice to have:
- Knowledge of the insurance domain.
- Experience with SQL Server Integration Services (SSIS) for developing and maintaining ETL packages and data integration workflows.