Informatica Python ETL Data Engineer & Tester

Infosys • Raleigh, AZ

7d

About The Position

As a Technology Consultant 2 in Infosys’s Financial Services unit, you will contribute to software and data engineering work supporting digital transformation projects for financial institutions. The role involves participating throughout the software development lifecycle, from requirements elicitation and design discussions through coding, testing, integration, deployment support, and production issue resolution.

You will focus on Informatica development and Python-based ETL and data test automation. This includes validating source-to-target mappings and transformations, reconciling data, testing data warehouses and migrations, validating Oracle databases and AWS data platforms, and supporting batch jobs and workflow monitoring. You will prepare and execute test strategies, analyze results, coordinate defect fixes, and document testing processes and technical work. You will also collaborate with business, development, and data engineering teams and help prepare training and support materials.

Infosys’s Financial Services unit works with banking, wealth management, and insurance organizations, using technologies including AI, cloud, and data-led innovation. The position may require relocation and/or travel to the work or project location. Candidates must be authorized to work in the United States without employer-based visa sponsorship; Infosys states it cannot provide immigration sponsorship now or in the future.

Requirements

• Informatica development experience.
• Python, AWS, SQL, Oracle, and GitLab skills.
• Experience with ETL testing, data warehouse testing, and data migration testing.
• Experience with Python-based ETL and data test automation for source-to-target validation, reconciliation, and regression testing.
• Ability to write SQL queries and validate Oracle databases.
• Knowledge of source-to-target mapping, transformation rule, data lineage, and business rule validation.
• Experience with data reconciliation, completeness checks, referential integrity validation, duplicate detection, and data quality testing.
• Knowledge of data warehousing concepts including facts, dimensions, star schema, and SCD validations.
• Ability to validate AWS data platforms.
• Experience with GitLab, batch job validation, workflow monitoring, and scheduling tools such as Autosys, Control-M, or Airflow.
• Python or Shell scripting skills for ETL and data validation activities.
• Experience preparing test strategies, executing test cases, analyzing results, and resolving defects.
• Ability to collaborate with business, development, and data engineering teams.
• Ability to document test scenarios, SQL validations, automation assets, and testing processes.
• Bachelor’s degree or foreign equivalent from an accredited institution, or three years of progressive experience in the specialty in lieu of each year of education.
• Authorization to work in the United States for any employer without employer-based visa sponsorship.

Nice To Haves

• BI reporting validation using Power BI, Tableau, Qlik, or MicroStrategy.
• Experience with big data technologies including Hadoop, Spark, Hive, and Kafka.
• Exposure to AI-enabled data quality and data governance solutions.
• Experience in banking, capital markets, wealth management, or mortgage domains.
• Exposure to Azure, Databricks, Snowflake, Redshift, PostgreSQL, BigQuery, or GCP.

Responsibilities

• Document assigned portions of business requirements as part of requirements elicitation.
• Facilitate software application design discussions and document design decisions.
• Participate in coding and integrate new features or updates into existing applications while maintaining system stability.
• Conduct code reviews, make changes to the codebase, and maintain code repositories.
• Implement test strategies, analyze results, and coordinate bug fixes to uphold software quality standards.
• Develop user training programs, documentation, and support frameworks for transitions to new software applications.
• Help resolve production issues and recommend preventive strategies to enhance system reliability.
• Maintain records of code, testing techniques, and support activities.
• Develop and perform Python-based ETL and data test automation for source-to-target validation, reconciliation, and regression testing.
• Validate source-to-target mappings, transformation rules, data lineage, business rules, data quality, and data warehouse structures.
• Perform SQL query writing and Oracle database validation, as well as AWS data platform validation.
• Validate batch jobs and monitor workflows and scheduling tools.
• Prepare test strategies, execute test cases, analyze results, and support defect resolution.
• Document test scenarios, SQL validations, automation assets, and testing processes.
• Collaborate with business, development, and data engineering teams.

Benefits

• Medical, dental, vision, and life insurance.
• Long-term and short-term disability coverage.
• Health and dependent care reimbursement accounts.
• Accident, critical illness, hospital indemnity, and legal insurance.
• 401(k) plan and contributions dependent on salary level.
• Paid holidays and paid time off.
• Competitive pay.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level