Sr Data Quality Engineer - SDET

Tatari•New York, NY

1d•$140,000 - $170,000•Hybrid

About The Position

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV. That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era. We are looking for a Sr. Data Quality Engineer to join the Reporting and Measurement Engineering team. In this role, you will build and maintain data validation frameworks, develop safeguards for critical measurement pipelines, and own testing strategy across our data infrastructure. You will partner with engineers, data scientists, and product managers to ensure the reliability and trustworthiness of the data powering Tatari's client-facing dashboards and analytics, where accuracy directly impacts how our clients measure the performance of their TV ad spend.

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
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

Nice To Haves

Experience with data quality frameworks such as Great Expectations is a strong plus

Responsibilities

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