AWS Python ETL Data Tester

Infosys • Raleigh, AZ

7d

About The Position

The AWS Python ETL Data Tester works as a Technology Consultant 2 on software and data-testing activities for Infosys Financial Services. The role contributes to requirements elicitation, application design discussions, coding and integration, code reviews, test strategy implementation, defect resolution, production support, and technical documentation. It supports the delivery of reliable data through ETL, data warehouse, data migration, and cloud-platform testing, while collaborating with business, development, and data engineering teams.

The role develops Python- and Shell-based automation for ETL testing and data validation; validates databases, source-to-target mappings, transformation rules, data lineage, and business logic; and performs reconciliation, completeness, referential-integrity, duplicate-detection, and data-quality checks. It also validates batch jobs and workflows, maintains testing documentation and automation assets, and may require relocation and/or travel to the work or project location.

Infosys Financial Services works with financial institutions on digital transformation using AI, cloud, and data-led innovation. Its projects span banking, wealth management, and insurance. Applicants authorized to work in the United States are encouraged to apply.

Requirements

• Experience in data/ETL testing.
• Experience in Python-based ETL test automation.
• Experience in ETL testing, data warehouse testing, and data migration testing.
• Ability to develop automation solutions using Python or Shell scripting for ETL and data validation.
• Experience with SQL and database validation across Oracle, SQL Server, PostgreSQL, Snowflake, AWS Redshift, or BigQuery.
• Ability to validate source-to-target mappings, transformation rules, data lineage, and business logic using mapping documents.
• Experience with data reconciliation, completeness checks, referential-integrity checks, duplicate detection, and data-quality validation.
• Experience with ETL tools such as Informatica, Ab Initio, ODI, SSIS, DataStage, Azure Data Factory, or Databricks.
• Strong understanding of data warehousing concepts, including facts, dimensions, star schema, and SCD validations.
• Experience validating cloud-based data platforms on AWS, Azure, Databricks, Snowflake, or GCP.
• Hands-on experience with batch-job validation, workflow monitoring, and scheduling tools such as Autosys, Control-M, or Airflow.
• Ability to implement test strategies, prepare and execute test cases, analyze results, and coordinate defect resolution.
• Ability to collaborate with business, development, and data engineering teams.
• 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.
• Applicants must be authorized to work in the United States.

Nice To Haves

• Experience validating BI reporting using Power BI, Tableau, Qlik, or MicroStrategy.
• Experience with Big Data technologies such as Hadoop, Spark, Hive, and Kafka.
• Knowledge of AI-enabled data quality and data governance solutions.
• Banking, Capital Markets, Wealth Management, or Mortgage domain experience.

Responsibilities

• Document assigned portions of business requirements as part of requirements elicitation.
• Facilitate software application design discussions and document design decisions for the technical team.
• 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, prepare and execute test cases, analyze results, and coordinate bug fixes or defect resolution.
• Develop user training programs, documentation, and support frameworks for transitions to new software applications.
• Help resolve production issues and recommend preventive strategies to improve system reliability.
• Maintain records of code, testing techniques, support activities, test scenarios, SQL validations, automation assets, and testing processes.
• Develop Python- and Shell-based automation for ETL and data validation activities.
• Test ETL processes, data warehouses, data migrations, and cloud-based data platforms.
• Validate source-to-target mappings, transformation rules, data lineage, and business logic against mapping documents.
• Perform data reconciliation, completeness checks, referential-integrity checks, duplicate detection, and data-quality validations.
• Validate batch jobs and monitor workflows and scheduling.
• Collaborate with business, development, and data engineering teams to ensure accurate and reliable data delivery.

Benefits

• Medical, dental, vision, and life insurance.
• Long-term and short-term disability insurance.
• 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