Lead Data Tester (Databricks)
Description
Salary: ₱130,000 – ₱145,000 per month
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