Must have skills : ETL, SQL, Python, Spark

Desirable skills : Big Data Tech Stacks

Infosys role : Quality Engineering Analyst, Quality Engineering Lead

Desired experience range : 4-8 years

Location(s) where this position can work out of : Bangalore, Chennai, Pune, Chandigarh, Hyderabad

Does this position require working from client office all or some days in the week? : No

Is remote working allowed : Yes (Hybrid model)

Responsibilities :

- Hands-on experience in ETL Testing, Data Warehouse Testing, and Data Migration Testing.

- Strong expertise in SparkSQL and database validation across Oracle, SQL Server, PostgreSQL, Snowflake, AWS Redshift, or BigQuery.

- Validate source-to-target mappings, transformation rules, data lineage, and business logic as per mapping documents.

- Experience in Python-based ETL test automation.

- Perform data reconciliation, completeness checks, referential integrity, duplicate detection, and data quality validations.

- 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 designing and implementing Spark-based Data Validation frameworks to validate large-scale financial data across batch and ETL pipelines, ensuring data quality, completeness, accuracy, and consistency throughout the project lifecycle.

- Experience developing automated data quality controls and validation test suites using Apache Spark, including reconciliation, schema validation, data profiling, and exception handling for high-volume financial datasets.

- 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.

- Develop automation solutions using Python/Shell scripting for ETL and data validation activities.

- 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.

Nice to Have Skills :

- 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.

Your Contribution to the Team :

- Strong analytical and problem-solving skills.

- Ability to understand complex business transformations and convert them into comprehensive test scenarios.

- Passion for ensuring data accuracy, integrity, and compliance.

- Proactive approach to identifying data defects and root cause analysis.

- Ability to collaborate effectively with Data Engineers, Architects, Business Analysts, and Product Owners.

Required/Basic Qualifications :

- Bachelor's degree or foreign equivalent required from an accredited institution.

- At least 4 years of experience in Data/ETL Testing.

- Strong experience in SQL, Data Validation, Data Reconciliation, Python.

- Experience working in Agile delivery environments.