Senior Quality Assurance Engineer, Data & Platform Engineering
LG Ad Solutions6 months ago
Denver, CO, USASenior
Responsibilities
- Design and lead test strategies for data pipelines and platform quality, including ETL validation, data quality checks, and pipeline observability.
- Build scalable test automation frameworks for unit, integration, and end-to-end testing of Spark jobs, Airflow DAGs, and backend services.
- Establish data quality gates for schema validation, data completeness, and consistency checks within development pipelines.
- Partner with data and platform engineers to define quality standards for features and infrastructure changes.
- Create quality instrumentation and metrics for pre-release and production systems, including anomaly detection and alerting.
- Identify architectural deficiencies affecting data quality and lead improvement initiatives.
- Design parallelized test plans for independent execution across teams in the United States and India.
- Mentor engineers on data mocking, test data management, pipeline idempotency testing, and related practices.
- Influence cross-team engineering decisions to improve product quality and reduce defect escape rates.
Requirements
- 7+ years of QA engineering experience, including meaningful experience testing data pipelines, backend services, or distributed systems.
- Ability to design and execute test plans for complex and ambiguous problem areas with limited guidance.
- Hands-on experience building extensible test automation frameworks from scratch.
- Working knowledge of ETL/ELT patterns, pipeline orchestration, data quality dimensions, and schema validation.
- Experience defining quality metrics, simplifying testing processes, and removing bottlenecks.
- Experience establishing quality gates in CI/CD pipelines using Jenkins, GitHub Actions, or similar tools.
- Strong judgment regarding short-term technical needs and long-term quality architecture.
- Ability to communicate testing strategy and quality risks to technical and non-technical stakeholders.
- Experience mentoring engineers and improving team testing capabilities.
- Familiarity with Apache Airflow, Apache Spark using PySpark or Scala, or Databricks is preferred.
- Experience testing AdTech systems such as DSP, SSP, ACR, or audience data platforms is preferred.
- Knowledge of cloud infrastructure testing on AWS, GCP, or Azure is preferred.
- Experience with data observability tools such as Great Expectations, Monte Carlo, or dbt tests is preferred.
- Understanding of distributed systems and their impact on testability is preferred.
- Experience with service virtualization, mock services, or chaos/resilience testing is preferred.
- A bachelor’s or master’s degree in Computer Science, Engineering, or a related field is preferred.
- Proficiency in Python or another scripting language for test tooling is preferred.
Benefits
- On-site work 4 days per week at the Denver office
- No relocation support offered
Tech Stack
Apache AirflowApache SparkAWSAzureDatabricksdbtGitHub ActionsGoogle Cloud PlatformJenkinsPythonScala
Categories
Data EngineeringTesting
About LG Ad Solutions
LG Ad Solutions builds a connected TV advertising and analytics platform that helps brands plan, target, and measure campaigns across smart TVs and digital video. It combines premium LG smart TV ad inventory with TV viewership data and attribution tools for cross-screen activation and reporting. Founded in 2013 and headquartered in Mountain View, it operates as a subsidiary of LG Electronics.