Intermediate Quality Engineer [T500-26957]

About CIBC: CIBC is a leading North American bank, with a history of more than 150 years of living our purpose - to help make your ambition a reality. Client relationships are at the center of our strategy, and our growth is enabled by a highly engaged and connected global team. From digital banking to community impact, we’re proud to drive progress for our clients and our communities.

Recognized for our culture, award-winning innovation and community investment, CIBC continues to evolve by putting people and progress at the centre of everything we do. About CIBC India: CIBC India is a technology and operations hub in Hyderabad, where you’ll be part of our highly engaged and global team, and play a central role in supporting our growth. Whether you’re driving innovation in digital banking or streamlining client onboarding, you’ll be part of a culture recognized for excellence and investment in people.

At CIBC India, people and progress are at the center of what we do: you’ll develop skills, collaborate with industry leaders, and see your ideas realized in a culture that values progress and belonging. We provide cutting-edge resources, ongoing learning, and a supportive environment where people come first. If you’re ready to create meaningful change and build your future, CIBC India is where your ambition meets opportunity.

What CIBC India Offers: At CIBC India, your goals are a priority. We start with your strengths and ambitions and strive to create opportunities to tap into your potential. We aspire to give you a career that goes well beyond your compensation.

We work to recognize you in meaningful, personalized ways including competitive fixed pay, performance-based incentive programs, a family-first benefits program, employer contributions for your retirement, attractive time off and leave offerings, wellbeing support, and MomentMakers, our social, points-based recognition program. Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients worldwide We cultivate a culture where you can express your ambition through initiatives like Purpose Day, a paid day off dedicated for you to use to invest in your growth and development. Intermediate Quality Engineer - ETL Automation experience – L6 Job Responsibilities: Required Skills: 5-8 years of experience in ETL/Data Engineering Testing with strong automation focus.

Strong hands-on expertise in SQL (complex joins, aggregations, performance tuning). Strong programming skills in Python (mandatory). Experience with PySpark or large-scale data processing frameworks.

Proven experience in ETL/data validation automation. Strong understanding of data pipelines, transformations, and data flows. Experience in data reconciliation and comparison techniques.

Knowledge of data quality frameworks and validation strategies. Experience working with multiple data sources (RDBMS, files, APIs, cloud storage). Experience with modern data platforms such as Databricks, Snowflakes or similar.

Exposure to data warehousing concepts (star/snowflake schema). Experience in automation framework design for data testing. Exposure to CI/CD pipelines for test automation.

Experience in reporting validation (Power BI or similar tools). Nice to Have: Experience working with large-scale data platforms or distributed systems and domain exposure to Banking or Financial data. Key Responsibilities: Perform end-to-end ETL/data pipeline testing across multiple data systems.

Design and build robust automation frameworks for data validation and reconciliation. Automate source-to-target data comparison, including large-scale data validation. Validate data transformations, mappings, and business rules.

Develop reusable automation scripts using Python and/or PySpark. Execute and optimize complex SQL queries for validation. Perform data quality checks, anomaly detection, and consistency validation.

Validate data across staging, warehouse, and reporting layers. Implement automated regression testing for data pipelines. Perform root cause analysis for data discrepancies and defects.

Work with structured and unstructured data sources (databases, files, APIs, cloud storage). Collaborate with data engineers, developers, and business stakeholders. Drive continuous improvement in automation coverage and testing processes.

Document frameworks, validation logic, and testing approaches.