Python ETL Data Tester

Infosys

About The Position

In the assigned Job Role of Technology Consultant 2, your Area Of Responsibility will be as below: . The Infosys Financial Services unit is a global leader in driving digital transformation for financial institutions. We specialize in leveraging advanced technologies suchA collaborative spirit and excellent communication skills. The ability to handle end-to-end SDLC phases from requirement gathering to implementation. A knack for translating complex requirements into actionable development tasks. A passion for design and hands-on coding experience. A proactive approach to testing, troubleshooting, and refining our applications. The ability to work with cross-functional teams and do software integration. The Infosys Financial Services unit is a global leader in driving digital transformation for financial institutions. We specialize in leveraging advanced technologies such as AI, cloud, and data-led innovation to help our clients accelerate growth and unlock business value. Our AI-driven solutions empower financial institutions to make smarter decisions, enhance customer experiences, and achieve operational excellence. Join us to be part of a pioneering team that is at the forefront of financial services transformation. You'll have the opportunity to work with cutting-edge AI technologies, collaborate with industry experts, and contribute to transformative projects across banking, wealth management, and insurance sectors. If you're passionate about AI and eager to make a significant impact, the Infosys Financial Services unit is the perfect place for you to grow and excel.

Requirements

Experience in Data/ETL Testing.
Experience in Python-based ETL test automation.
Experience in ETL Testing, Data Warehouse Testing, and Data Migration Testing.
Experience in SQL and database validation across Oracle, SQL Server, PostgreSQL, Snowflake, AWS Redshift, or BigQuery.
Experience in 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.
Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.

Nice To Haves

Experience in BI Reporting validation using Power BI, Tableau, Qlik, or MicroStrategy.
Experience in 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

Contribute to the requirements elicitation process by documenting assigned parts of business requirements, in line with guidance provided
Facilitate software application design discussions, and document design decisions to guide the technical team towards building software solutions
Participate in coding and integrate new features or updates into existing applications, with a focus on maintaining system stability
Conduct code reviews, do changes to the codebase and maintain code repositories
Implement test strategies, analyse results, and coordinate bug fixes to uphold the software quality standards
Develop user training programs, documentation, and support frameworks to ensure a smooth transition to new software applications
Actively participate in resolving production issues and recommend preventive strategies to enhance system reliability
Maintain detailed records of code, testing techniques, and support activities to enrich the knowledge base and assist other similar projects
Develop automation solutions using Python/Shell scripting for ETL and data validation activities.
Validate source-to-target mappings, transformation rules, data lineage, and business logic as per mapping documents.
Perform data reconciliation, completeness checks, referential integrity, duplicate detection, and data quality validations.
Implement test strategies, prepare and execute test cases, analyze results, and coordinate defect resolution to ensure data quality.
Collaborate with business, development, and data engineering teams to ensure accurate and reliable data delivery.
Maintain detailed documentation of test scenarios, SQL validations, automation assets, and testing processes.