Lead Data Engineer (Banking)

Role: Lead Data Engineer (Banking) Must-have skills Banking and domain • Production delivery of data pipelines inside banks. • Customer, account, transaction, payments and AML data. • Working within bank release, scheduling and change controls. Core data engineering • Teradata SQL, BTEQ, TPT and FastLoad/MultiLoad; query tuning. • Spark (PySpark/Scala), Hive, Impala, HBase, Pig and Hue; Apache Iceberg and Trino; Python and R. • Historical data processing: snapshots, SCD Type 2 and multi-grain backfills with control totals and validation reports. • ETL/ELT development, CDC, metadata-driven automation frameworks and parameter-driven SQL generation. • Reconciliation, data quality and SLA monitoring. • Performance at scale: tables of 1 billion+ rows and multi-year history. Requirements Experience: Lead: 12+ years, including 6+ in banking. Senior: 8+ years, including 4+ in banking · Banking and domain • Production delivery of data pipelines inside banks. • Customer, account, transaction, payments and AML data. • Working within bank release, scheduling and change controls. Core data engineering • Teradata SQL, BTEQ, TPT and FastLoad/MultiLoad; query tuning. • Spark (PySpark/Scala), Hive, Impala, HBase, Pig and Hue; Apache Iceberg and Trino; Python and R. • Historical data processing: snapshots, SCD Type 2 and multi-grain backfills with control totals and validation reports. • ETL/ELT development, CDC, metadata-driven automation frameworks and parameter-driven SQL generation. • Reconciliation, data quality and SLA monitoring. • Performance at scale: tables of 1 billion+ rows and multi-year history. Integration and platforms • Kafka, Spark Streaming, Informatica (PowerCenter, IDMC, IDL) and Talend; REST API development. • Denodo, Snowflake and NoSQL databases. • Airflow, Control-M or Autosys; Git, CI/CD, GitOps and Kubernetes. Delivery and communication (Lead) • Framework design, code standards, code reviews and estimation. • Guiding a team of engineers and working with architects and analysts. Good-to-have skills • Databricks: Delta Lake, Unity Catalog and Workflows. • Data services on Azure, Google Cloud, Huawei Cloud or Alibaba Cloud. • Data modelling for Qlik Sense or Power BI. Certifications (preferred): Teradata Vantage; Cloudera Data Engineer; Databricks Data Engineer Associate or Professional