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- Same hard prerequisite: financial services background mandatory (JD lists it as desired; overridden by client rule)
- 5+ years in IT/Data; Bachelor in IT or related field
- Proficient PySpark for distributed computing and Python for ETL development
- Strong SQL: complex query writing and optimization (PostgreSQL, MySQL, Oracle or Snowflake)
- Data warehousing concepts and platforms, ideally Databricks; lakehouse modeling
- Financial markets data familiarity: securities, prices, corporate actions, positions/holdings
- Dimensional modelling, normalization/denormalization, schema design
- Data quality frameworks (ideally Monte Carlo); pipeline monitoring (Prometheus, Grafana)
- End-to-end ownership from vendor/internal ingestion to discoverability, reliability and cost efficiency; L3 prod incident resolution
- Git, unit/integration testing, Agile (Azure DevOps, Jira/Confluence)
