Role & responsibilities
- Focus on major areas of work, typically 20% or more of role % of
- Time
- Lead and mentor a team of Data Quality Engineers supporting multiple data teams and projects. Define team goals, manage performance, and guide career growth- 30%
- Drive test automation strategy across data pipelines (e.g., Snowflake, Databricks, Airflow). Define validation frameworks, regression practices, and CI/CD integration- 30%
- Collaborate with Data Engineers, Product Managers, and Analysts to ensure data correctness, integrity, and trustworthiness at every stage of the pipeline- 20%
- Actively contribute to the development and improvement of testing frameworks and engineering processes to scale quality efforts- 10%
- Participate in hiring efforts and contribute to long-term team planning and cross- 10%
Preferred candidate profile
- 8+ years of hands-on experience in software testing or data engineering, with at least 2 years in technical leadership or management roles.
- Proven experience validating complex ETL pipelines, business logic, and data transformations across large-scale systems.
- Proficiency in Python and SQL, including working with terabyte-scale datasets to identify data anomalies and logic issues.
- Strong understanding of data quality automation frameworks, CI/CD pipelines, and tools like Airflow, Spark, Databricks, or Snowflake.
- Experience driving quality best practices within Agile teams and participating in cross- functional planning and delivery.
- Demonstrated ability to manage, mentor, and grow engineering talent, fostering a culture of accountability and collaboration.
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
