Data Engineer
Core
Design, build, test, and maintain scalable data pipelines and ETL/ELT processes to integrate data from multiple sources for analytics, reporting, and business decision-making in a banking environment.
Role type
Data Engineer
Builds
Reliable data pipelines, data models, and integrated data solutions for analytics and reporting
Domain
Banking / Financial Services / Data Engineering
Deliverable
production ML models | product features | dashboards & analysis
Required skills
SQL, ETL/ELT pipeline development, data warehousing, data lakes/lakehouse environments, data modeling, Python, PySpark, Spark, data quality checks, pipeline monitoring, data governance
Preferred skills
Azure Data Factory, Databricks, Synapse, Microsoft Fabric, AWS Glue, Redshift, BigQuery, Snowflake, Scala, data analysis, financial services domain experience
Technologies
SQL, T-SQL, Python, PySpark, Spark, Databricks, Azure Data Factory, Azure Synapse, Microsoft Fabric, Snowflake, BigQuery, Redshift, Git, CI/CD, Power BI
Responsibilities
Design and maintain data pipelines and ETL/ELT processes; Develop and optimize SQL queries and data transformation logic; Support data integration between operational systems, warehouses, and reporting platforms; Monitor pipelines for failures and performance issues; Troubleshoot production data issues; Document data flows and technical designs; Support data governance and security requirements
Seniority
Mid-level, hands-on IC
