Data/ETL test lead

Agile Scrum Ceremonies, Testing Collaboration & Team Execution:

• Actively participate in Sprint Planning by analyzing user stories, defining acceptance criteria, and estimating testing efforts using story points.
• Attend Daily Stand-ups to communicate testing progress, identify blockages, and surface data dependencies.
• Contribute to Backlog Grooming and Sprint Retrospectives to continuously refine team processes and Data Migration / ETL testing workflows.
• Collaborate early with developers and data engineers to support effective testing and accelerate defect resolution.
• Track, manage, and log defects across the full defect lifecycle using tools such as Service Now, Jira, or Azure DevOps.

ETL & Data Validation Testing:

• Review Source-to-Target Mapping (STM) documentation and business rules to create comprehensive, reliable test scenarios.
• Develop and run advanced SQL queries to verify data, perform record counts, and reconcile information between source systems, staging environments, and data warehouses/marts.
• Validate data transformations, including aggregations, filtering logic, and boundary conditions.
• Ensure data integrity by performing checks for data truncation, NULL-value handling, and duplicate records.

Automation (Good to have):

• Build, maintain, and execute automated ETL test scripts using frameworks such as Pytest, Python, or Java.
• Implement testing routines within CI/CD pipelines, including Jenkins, Azure DevOps, or GitHub Actions.

Required Qualifications & Skills:

• Experience: 8+ years of hands-on experience in ETL/Data Warehouse testing and backend data validation.
• Agile Knowledge: Proven experience working in an Agile/Scrum software development lifecycle.
• Database & SQL: Advanced SQL querying skills across relational databases (SQL Server, Oracle, PostgreSQL) or cloud platforms (GCP, Snowflake, Databricks, AWS/Azure).
• ETL Tools: Familiarity with enterprise ETL tools (Informatica, SSIS, Talend, or AWS Glue) or cloud data processing frameworks.
• Soft Skills: Strong analytical, communication, and problem-solving capabilities to bridge technical requirements with business stakeholders.
• Good to have:
• Scripting: Basic to intermediate programming skills in Python or Java for test automation

Key Responsibilities:

• Lead a team of data/ETL testers
• Own test strategy & planning
• Drive test reporting & governance
• Actively participate in Sprint Planning to analyze user stories, define acceptance criteria, and estimate testing efforts (story points).
• Attend Daily Stand-ups to report testing progress, blockages, and data dependencies.
• Engage in Backlog Grooming and Sprint Retrospectives to continuously improve team processes and Data Migration / ETL testing workflows.
• Collaborate proactively with developers and data engineers to enable early testing and rapid defect resolution.
• Track, manage, and log defects throughout the defect lifecycle using tools such as Service Now, Jira or Azure DevOps.

ETL & Data Validation Testing:

• Review Source-to-Target Mapping (STM) documents and business rules to design robust test scenarios.
• Write and execute complex SQL queries for data verification, counts, and reconciliation between source systems, staging areas, and data warehouses/marts.
• Validate data transformations, aggregations, filtering logic, and boundary conditions.
• Perform data integrity validation including data truncation, NULL-value handling, and duplicate checks.
• Conduct cutover and production migration validation

Automation (Good to have):

• Build, maintain, and execute automated ETL test scripts using frameworks like Pytest, Python, or Java.
• Integrate testing routines within CI/CD pipelines (Jenkins, Azure DevOps, or GitHub Actions).

Required Qualifications & Skills:

• Experience: 8+ years of hands-on experience in ETL/Data Warehouse testing and backend data validation.
• Agile Knowledge: Proven experience working in an Agile/Scrum software development lifecycle.
• Database & SQL: Advanced SQL querying skills across relational databases (SQL Server, Oracle, PostgreSQL) or cloud platforms (GCP, Snowflake, Databricks, AWS/Azure).
• ETL Tools: Familiarity with enterprise ETL tools (Informatica, SSIS, Talend, or AWS Glue) or cloud data processing frameworks.
• Soft Skills: Strong analytical, communication, and problem-solving abilities to bridge technical gaps with business stakeholders.

Good to have:

• Scripting: Basic to intermediate programming skills in Python or Java for test automation