Lead Data Tester

Key responsibilities

• 10+ years in software or data quality assurance, with 4+ years leading QA teams in a data engineering or data warehousing environment

• Proven track record establishing or transforming a QA practice, including shift-left or test-driven approaches and QA embedded in agile delivery teams

• Develop and maintain automated data quality tests, data validation scripts, and monitoring solutions

• Oversee and mentor junior QA testers, providing guidance on best practices, methodologies, and professional development

• Conduct thorough data integrity testing across multiple data pipelines, data lakes, and warehouse environments

• Collaborate with data engineers, software developers, and business stakeholders to define data quality requirements and acceptance criteria

• Identify, document, and report data quality issues, anomalies, and discrepancies with clear impact assessments

• Perform root cause analysis on data failures and work with cross-functional teams to implement corrective actions

• Establish and maintain data testing documentation, test cases, and quality metrics dashboards

• Participate in the evaluation and implementation of data testing tools and technologies

• Lead continuous improvement initiatives to enhance testing efficiency, coverage, and effectiveness

What we're looking for

• Proven expertise with Databricks platform, including data validation and quality testing within Databricks environments

• Hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog, Databricks Workflows/Jobs) or other Big Data/Spark platforms

• Banking or financial services industry experience

• Experience with data quality frameworks and CI/CD quality gates for data pipelines

• Strong knowledge of SQL and data manipulation languages for writing complex data validation queries

• Demonstrated experience with automated testing frameworks, tools, and scripting languages such as Python, Scala, or Java

• Solid understanding of data warehouse concepts, ETL processes, and data pipeline architectures

• Experience with data quality tools and frameworks such as Great Expectations, dbt, or similar platforms

• Leadership experience with the ability to mentor and guide junior team members effectively

• Strong analytical and problem-solving skills with excellent attention to detail

• Excellent communication skills and ability to work collaboratively across technical and non-technical teams

• Familiarity with version control systems such as Git

• Preferred: Experience with cloud platforms such as AWS, Azure, or GCP

• Preferred: Knowledge of Agile or DevOps methodologies

• Preferred: Relevant certifications in QA, data management, or Databricks training