Capgemini-posted 1 day ago
Full-time • Mid Level
Dallas, TX
5,001-10,000 employees

Design and implement scalable ETL pipelines on Databricks (PySpark, SQL, Delta Lake) to process credit card transactions, balances, and payments. Develop the core calculation engines and integrate with upstream/downstream systems. Optimize Spark jobs for large-scale financial datasets (billions of records, partitioning, caching, AQE). Ensure data quality and reconciliation across raw, curated, and output layers. Implement parameterized rules (APR, compounding frequency, grace period logic). Collaborate with business analysts to translate product rules into technical implementations. Apply unit tests, CI/CD pipelines, and monitoring for production-grade pipelines. Ensure compliance with financial data governance, lineage, and audit requirements.

  • Design and implement scalable ETL pipelines on Databricks (PySpark, SQL, Delta Lake) to process credit card transactions, balances, and payments.
  • Develop the core calculation engines and integrate with upstream/downstream systems.
  • Optimize Spark jobs for large-scale financial datasets (billions of records, partitioning, caching, AQE).
  • Ensure data quality and reconciliation across raw, curated, and output layers.
  • Implement parameterized rules (APR, compounding frequency, grace period logic).
  • Collaborate with business analysts to translate product rules into technical implementations.
  • Apply unit tests, CI/CD pipelines, and monitoring for production-grade pipelines.
  • Ensure compliance with financial data governance, lineage, and audit requirements.
  • Strong in PySpark, SQL, Databricks (clusters, notebooks, Delta Live Tables, Unity Catalog).
  • Hands-on experience with credit card or banking domain data (balances, minimum payments, billing cycles).
  • Expertise in data modeling, partitioning, and query performance tuning.
  • Experience with workflow orchestration (Airflow, Databricks Workflows, Dagster).
  • Knowledge of CI/CD (Bitbucket/GitHub, Jenkins, Terraform for infra-as-code).
  • 6-10 years of experience in Data Engineering (preferably financial services).
  • Flexible work
  • Healthcare including dental, vision, mental health, and well-being programs
  • Financial well-being programs such as 401(k) and Employee Share Ownership Plan
  • Paid time off and paid holidays
  • Paid parental leave
  • Family building benefits like adoption assistance, surrogacy, and cryopreservation
  • Social well-being benefits like subsidized back-up child/elder care and tutoring
  • Mentoring, coaching and learning programs
  • Employee Resource Groups
  • Disaster Relief
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