Data Engineer
Core
Design, build, test, and maintain scalable data pipelines and ETL/ELT processes to integrate data from multiple sources for banking analytics and reporting.
Role type
Data Engineer
Builds
Reliable data pipelines, data models, and integration between operational systems, data warehouses, lakes, and reporting platforms.
Domain
Banking / Financial Services
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
Preferred skills
Azure Data Factory, Databricks, Synapse, Microsoft Fabric, AWS Glue, Redshift, BigQuery, Snowflake, Scala, data analysis, data exploration, data governance, security, access control, compliance
Technologies
Azure Data Factory, Databricks, Synapse, Microsoft Fabric, AWS Glue, Redshift, BigQuery, Snowflake, Spark, PySpark, Python, SQL, T-SQL
Responsibilities
Design, build, test, and maintain data pipelines and ETL/ELT processes; Extract, transform, and load data from multiple source systems; Develop and optimise SQL queries, stored procedures, and data transformation logic; Support data integration between operational systems, data warehouses, lakes, and reporting platforms; Build and maintain data models to support analytics, reporting, and downstream consumption; Monitor data pipelines for failures, performance issues, and data quality concerns; Troubleshoot and resolve data-related production issues; Support data governance, security, access control, and compliance requirements; Document data flows, data definitions, technical designs, and support procedures; Contribute to automation, performance optimisation, and continuous improvement of the data platform; Support data analysis requirements to enable business insights and decision-making
Seniority
Mid-level (3+ years experience)
