Data Engineer

Job Description:

• Design, develop, and maintain Azure Databricks pipelines for credit card data ingestion, transformation, integration, and downstream consumption
• Develop scalable processing solutions using PySpark, Python, Spark SQL, SQL, Delta Lake, and ADLS for high-volume card datasets
• Build transformation logic for cardholder, account, transaction, authorization, payment, balance, fee, interest, rewards, and servicing data
• Translate business requirements and source-to-target mappings into reusable Databricks notebooks, workflows, jobs, and ETL/ELT processes
• Support credit card platform conversion and modernization, including data mapping, historical/incremental loads, transformation, and reconciliation
• Implement automated data quality, balancing, reconciliation, cleansing, and exception-handling controls across source and target environments
• Protect sensitive cardholder information, including PAN and PCI-sensitive data, through masking, tokenization, encryption, and appropriate data-handling practices
• Troubleshoot and optimize Databricks pipelines
• Collaborate with credit card SMEs, architects, analysts, and application teams
• Build innovative solutions and relationships with teammates and clients while accessing global capabilities

Requirements:

• 5+ years of Data Engineering, ETL/Data Warehouse, or Big Data experience, including 3+ years of hands-on Azure Databricks development
• Strong hands-on development experience with Databricks, PySpark, Python, Spark SQL, SQL, Delta Lake, and ADLS
• Experience designing and developing scalable ETL/ELT pipelines for large-volume transactional and financial datasets
• Strong experience with data transformation, source-to-target mapping, cleansing, reconciliation, data quality, and exception handling
• Credit card/payments domain experience with knowledge of card accounts, transactions, authorizations, payments, balances, billing, and settlement
• Experience with Azure DevOps, Git, CI/CD, and Agile/Scrum development practices
• Strong banking/financial services experience and understanding of financial data controls and reconciliation
• Experience with TSYS or another major credit card processing platform preferred
• Experience supporting credit card conversions, migrations, or platform modernization preferred
• Knowledge of the end-to-end card lifecycle preferred
• Experience with Mastercard and/or Visa data, interfaces, reporting, rewards, or loyalty programs preferred
• Understanding of PCI DSS, PAN protection, tokenization/detokenization, encryption, and sensitive cardholder data management preferred
• Experience with advanced Databricks capabilities such as Unity Catalog, Workflows, Auto Loader, and Lakeflow/Delta Live Tables preferred
• Experience modernizing Informatica PowerCenter or SSIS workloads to Databricks/PySpark preferred
• Azure and/or Databricks certifications and experience with large-scale banking conversion initiatives preferred
• Ability to successfully complete a background investigation
• Qualified applicants must meet applicable U.S. employment requirements

Benefits:

• Competitive compensation
• Comprehensive insurance options
• Matching contributions through the 401(k) plan and the share purchase plan
• Paid time off for vacation, holidays, and sick time
• Paid parental leave
• Learning opportunities and tuition assistance
• Wellness and Well-being programs
• Ownership opportunity from day 1 through CGI Partners model
• Global capabilities and industry and technology expertise
• Career development and skill-building opportunities
• Reasonable accommodations for qualified individuals with disabilities