Senior Quality Assurance Engineer, Data & Platform Engineering

We require people to be on-site, 4 days/week at our Denver or NYC office and are unable to offer relocation support.LG Ad Solutions is a global leader in connected TV (CTV) and cross-screen advertising. We pride ourselves on delivering state-of-the-art advertising solutions that integrate seamlessly with today's ever-evolving digital media landscape.The OpportunityWe are looking for a Senior QA Engineer to be the quality leader embedded directly within our Data & Platform Engineering team. This team builds and owns terabyte-scale data pipelines, platform tooling, and data governance frameworks that sit at the core of our advertising technology. You will work shoulder-to-shoulder with data engineers, understand the complexity of distributed systems and large-scale ETL workflows, and own quality from design through production.This is not a generic QA role. You will need to speak the language of data engineering—Apache Airflow, Spark, Databricks, cloud infrastructure—and bring a testing mindset that addresses the unique challenges of high-volume, high-velocity data systems. If you thrive on ambiguity, care deeply about quality at scale, and want your work to directly impact advertising revenue, this role is for you.What You’ll DoDesign and lead comprehensive test strategies for complex, ambiguous data pipeline and platform quality challenges, including ETL validation, data quality checks, and pipeline observabilityBuild scalable, maintainable test automation frameworks tailored to distributed data systems—covering unit, integration, and end-to-end testing of Spark jobs, Airflow DAGs, and backend servicesEstablish and own data quality gates within CI/CD pipelines, ensuring schema validation, data completeness, and consistency checks are embedded throughout the development lifecyclePartner closely with Data Engineers, Platform Engineers, and the hiring manager to define the quality bar for new features and infrastructure changesCreate instrumentation and metrics to measure quality both pre-release and in production, including anomaly detection and alerting across our data ecosystemProactively identify architectural deficiencies affecting data quality and lead initiatives to address themDrive parallelized test plan design to enable independent execution across a globally distributed team (US and India)Mentor engineers on testing best practices specific to data systems—data mocking, test data management, pipeline idempotency testing, and moreInfluence engineering decisions across team boundaries to continuously improve product quality and reduce defect escape ratesWhat You Bring7+ years of QA engineering experience, with meaningful time spent testing data pipelines, backend services, or distributed systemsProven ability to design and execute test plans for complex, ambiguous problem areas with limited guidanceHands-on experience building extensible test automation frameworks from scratch, not just maintaining existing onesWorking knowledge of data engineering concepts: ETL/ELT patterns, pipeline orchestration, data quality dimensions (completeness, consistency, timeliness), schema validationDemonstrated ability to define and implement quality metrics, simplify testing processes, and remove bottlenecksExperience establishing quality gates in CI/CD pipelines (Jenkins, GitHub Actions, or similar)Strong judgment on technical trade-offs between short-term needs and long-term quality architectureClear communicator who can convey testing strategy and quality risks to both technical and non-technical stakeholdersExperience mentoring engineers and improving overall team testing capabilitiesNice to HaveFamiliarity with Apache Airflow, Apache Spark (PySpark or Scala), or DatabricksExperience testing AdTech systems (DSP, SSP, ACR, or audience data platforms)Knowledge of cloud infrastructure testing on AWS, GCP, or AzureExperience with data observability tools (Great Expectations, Monte Carlo, dbt tests, or similar)Understanding of distributed systems concepts and how they impact testabilityExperience with service virtualization, mock services, or chaos/resilience testingBachelor’s or Master’s degree in Computer Science, Engineering, or related fieldProficiency in Python or another scripting language for test toolingLG Ad Solutions provides equal work opportunities to all team members and applicants, and it prohibits discrimination and harassment of any type on the basis of race, color, ethnicity, caste, religion, age, sex (including pregnancy), national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by our policies or federal, state, or local laws.We want to ensure that our hiring process is accessible. If you need reasonable accommodation for any part of the application process because of a medical condition or disability, please send an email to careers@lgads.tv to let us know the nature of your request.