We are seeking a highly skilled Data Engineering Developer with strong experience in banking operations, change management processes, and data pipeline development. The ideal candidate will design, build, and optimize end-to-end data ingestion pipelines, develop compute tables, support regulatory and business reporting, and collaborate with cross-functional teams to deliver high-quality analytics and dashboards.* Data Engineering & Pipeline Development* Design, develop, and maintain scalable ETL/ELT pipelines for ingesting structured and unstructured data from multiple banking systems.* Build data ingestion frameworks, orchestration workflows, and automated validation checks to ensure high data quality.* Develop compute tables, curated datasets, and semantic layers to support analytics, dashboards, and business workflows.* Optimize pipeline performance, automate repeatable processes, and ensure adherence to data governance and lineage standards.* Maintain CI/CD pipelines for data engineering code deployment, ensuring safe and compliant delivery within ChangeTechnical Skills Requirements* Core Data Engineering* SQL (advanced), PL/SQL, stored procedures Python / PySpark / Scala* ETL/ELT tools (Informatica, DataStage, Airflow, NiFi, or equivalent)Big Data platforms: Hadoop, Hive, HDFS, Spark* Cloud platforms: AWS / GCP / Azure (preferred: data lake, data warehouse, storage, compute)* Familiarity with Data Warehousing concepts (Kimball, Star/Snowflake schemas)* Data Pipeline & Orchestration* Workflow tools: Apache Airflow, Oozie, Control-M, or equivalent* CI/CD with Jenkins, Bitbucket* Data governance & quality frameworks (DQ rules, lineage, metadata)* Visualization & Reporting Tools - Power BI, Tableau, or Qlik-en
