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Tatari
Sr Data Quality Engineer - SDET
pythonsqlpytestdata qualitydata validationdata pipelinesAirflowDatabricksGreat Expectationscloud data infrastructuredata engineeringtestingautomationdata sciencehybrid
Key details
Salary
$140K – $170K
Employment type
Full-time
Seniority
Senior
Years experience
5-10
Location
Los Angeles, California, United States
Full job description
Tatari is seeking a Senior Data Quality Engineer to join the Reporting and Measurement Engineering team. The role involves building and maintaining data validation frameworks, developing automated data quality checks, owning pytest infrastructure improvements, collaborating with engineers, data scientists, and product managers to ensure data reliability, adopting data quality and lineage tools, defining data quality standards, monitoring pipeline health, and mentoring engineers on data quality best practices. Requirements include 5+ years of relevant experience, proficiency in Python and SQL, experience with test automation frameworks like pytest, familiarity with data pipeline orchestration tools such as Airflow and Databricks, knowledge of data quality frameworks like Great Expectations, strong communication skills, and a BS/MS in Computer Science or related field. Benefits include total compensation of $140,000-170,000 annually, equity, health insurance, 401K, FSA, commuter benefits, monthly spending account, education benefit, productivity perk, unlimited PTO, wellness days, office snacks and lunches, team events, and a hybrid work model with 2 days per week in office.
What you'll do
- Build and maintain data validation frameworks for critical measurement and reporting pipelines
- Develop automated data quality checks across ingestion, transformation, and reporting layers
- Own pytest infrastructure improvements and drive integration testing patterns across the engineering org
- Partner with engineers, data scientists, and product managers to debug complex data issues and define data quality standards
- Evaluate, adopt, and own data quality and lineage tooling to improve pipeline observability and traceability
- Define and enforce data quality standards for new feature launches and pipeline changes
- Monitor pipeline health and build alerting for data anomalies in collaboration with SRE
- Mentor engineers across the org on data quality best practices and contribute to a culture of testing excellence
Requirements
- 5+ years in data quality engineering, data engineering, or backend engineering with a strong focus on automated testing and data validation
- Strong proficiency in Python and SQL, including experience with relational and cloud-hosted databases
- Experience building test automation and validation frameworks for data pipelines, APIs, and microservices using pytest or similar tools
- Experience with data pipeline orchestration tools (e.g., Airflow, Databricks) and cloud data infrastructure
- Experience with data quality frameworks such as Great Expectations is a strong plus
- Comfortable working across engineering, data science, and product to communicate data quality standards and tradeoffs to both technical and non-technical stakeholders
- Detail-oriented with strong analytical skills and a genuine commitment to data accuracy and engineering excellence
- BS/MS in Computer Science, Engineering, or a related field, or equivalent practical experience
Tech stack
PythonSQLpytestAirflowDatabricksGreat Expectationscloud data infrastructure
Benefits
Total compensation ($140,000-170,000 annually)Equity compensationHealth insurance coverage for you and your dependents401K, FSA, and commuter benefits$150 monthly spending account$1,000 annual continued education benefit$500 Newbie Productivity PerkUnlimited PTO and sick daysMonthly Company Wellness Day OffSnacks, drinks, and catered lunches at the officeTeam building eventsHybrid RTO of 2 days per week in office
Apply now
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