Data Engineer

LouisianaNOW.Jobs

. Design, develop, and maintain Azure Databricks pipelines for credit card data ingestion, transformation, integration, and downstream consumption .

Posted 10/25/2026full-timeRemote • United StatesMid-LevelSenior💰 $72,500 - $160,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing scalable Azure Databricks pipelines for credit card data processing, with a strong focus on data transformation, quality controls, and compliance with PCI DSS standards. Proven ability to collaborate with cross-functional teams and translate business requirements into effective ETL/ELT solutions.

Highest-signal resume keywords

Azure Databricks DevelopmentPySpark ProgrammingData Transformation and CleansingCredit Card Domain ExperienceETL/ELT Pipeline Design

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Azure DatabricksPySparkPythonSpark SQLSQLDelta LakeADLSData Quality ControlsETL/ELT ProcessesData Mapping

Soft Skills

CollaborationProblem-SolvingCommunicationRelationship BuildingTroubleshooting

Tools & Technologies

Azure DevOpsGitCI/CDAgile/ScrumInformatica PowerCenterSSIS

Certifications & Qualifications

Azure CertificationDatabricks Certification

Industry Keywords

Credit Card ProcessingFinancial ServicesPCI DSSTokenizationCardholder Data ManagementMastercardVisaPaymentsBanking ConversionData Governance

Tech Stack

Tools & technologies

AzureETLInformaticaPySparkPythonSparkSQLSSISUnity

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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