Lead Data Quality Engineer

peopleimpact

Required skills

Responsibilies include:

Lead the design and implementation of test strategies for complex data pipelines and business logic.
Collaborate with cross-functional teams to ensure scalable, testable data solutions.
Architect and evolve automated testing frameworks across batch and streaming data.
Define and enforce best practices for testing, monitoring, and CI/CD in data workflows.
Own and drive strategic data quality initiatives, including stakeholder alignment and execution.
Mentor engineers, conduct code/test reviews, and support team development.
Manage direct reports as needed, including coaching, planning, and performance support.
Introduce and evaluate tools and frameworks to enhance test coverage and automation

Required Education, Experience/Skills/Training:

Experience in data quality engineering, software testing, or data engineering.
Strong proficiency in SQL and Python with the ability to validate large datasets.
Experience with Snowflake, Databricks, Spark, Airflow, or similar tools.
Proven ability to build and scale automated data testing frameworks.
Experience leading strategic initiatives and/or managing engineering team members.
Strong problem-solving and debugging skills; able to anticipate and prevent data issues.
B.S. in Computer Science (or equivalent degree or work experience)

Nice to have:

Experience with BDD frameworks (e.g., Behave)
Experience working in AWS or other cloud environments
Familiarity with open-source data quality tools like Deequ, Great Expectations, or similar custom frameworks

MNC

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