Lead Data Engineer (Banking)

Production delivery of data pipelines inside banks

Customer, account, transaction, payments and AML data

Working within bank release, scheduling and change controls

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

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

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

Core data engineering

Production delivery of data pipelines inside banks

Customer, account, transaction, payments and AML data

Working within bank release, scheduling and change controls

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

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

Core data engineering

Production delivery of data pipelines inside banks

Customer, account, transaction, payments and AML data

Working within bank release, scheduling and change controls

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

#J-18808-Ljbffr