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Position Name: Senior Engineer - Testing
| About Voya India: Voya India (earlier VFISLK) started out as a joint venture between U.S. financial services company Voya Financial and SLK, a software services company and is head quartered at Bangalore. As of Aug 2023, we are a wholly owned subsidiary of Voya Financial. We are a dynamic technology & business process transformation company that provides world-class technology & business process management services, with an emphasis on quality, speed & optimization driven through automation. We support and deliver innovative solutions to Voya’s Retirement, Employee Benefits, and Investment Management businesses. More information about us is available at: https://www.voyaindia.com |
| A highly skilled Quality Engineer specializing in data and ETL testing within modern cloud-based data platforms, with strong expertise in Databricks, PySpark, Python, and advanced SQL (Spark SQL). The role focuses on ensuring the accuracy, integrity, and reliability of large-scale data pipelines through comprehensive validation, automation, and performance optimization. This position is responsible for end-to-end testing of ETL/ELT pipelines, including source-to-target validation, data reconciliation, and data quality assurance across complex data ecosystems. |
| • 5+ years of experience in Data/ETL testing using Databricks, PySpark, and Python with strong automation exposure • Strong expertise in Advanced SQL (Spark SQL) for data validation, reconciliation, and performance tuning • Hands-on experience in end-to-end testing of ETL/ELT pipelines implemented using PySpark and Delta Lake • Experience in building/using data validation frameworks (PySpark, Python, /automation frameworks) • Ensure source data quality by validating accuracy, completeness, null values, duplicates, and consistency before ingestion into Databricks pipelines to prevent downstream data issues • Solid knowledge of STLC, test planning, estimation, and data testing strategies • Strong capability in source-to-target validation, data quality checks, and large-scale data analysis • Working knowledge of Databricks architecture (clusters, notebooks, jobs) and cloud ecosystem (ADLS, ADF, Snowflake basics) • Experience in data migration testing (DB2/Oracle to Databricks) and reconciliation strategies • Good understanding of PySpark transformations, joins, aggregations, and performance optimization techniques • Exposure to MDM testing and modernized data platforms is an added advantage • Strong communication skills with ability to analyze business requirements and work in Agile environments |
| • Bachelor's degree in Computer Science, Engineering, or a related field; Master's Degree preferred |
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