Sr. QA Engineer

Starz • Greenwood Village, CO

1d

About The Position

The STARZ Data Products & Engineering team is seeking a Senior QA Data Engineer who is passionate about ensuring data quality, integrity, and trust at scale. In this role, you will design and build data testing frameworks—primarily using Snowflake and supporting scripting pipelines—to ensure our ETL/ELT processes deliver timely, accurate, and reliable data products across the organization. You will work across a diverse data ecosystem, validating data ingestion and transformation from database systems, vendor-supplied files, API endpoints, and AWS S3. Partnering closely with Data Engineering and Business Intelligence teams, you will embed data quality checks early in the development lifecycle and help establish consistent QA standards that scale across teams. Our data pipelines support the entire organization, making data integrity a critical and highly visible responsibility. Strong experience with Snowflake or equivalent cloud data platforms is preferred.

Requirements

• 6+ years of experience in a senior-level QA role on a technical team, preferably within data engineering or analytics
• Bachelor’s degree in Information Management, Computer Science, Mathematics, Statistics, or a related technical field (or equivalent experience)
• Data Warehousing & Pipelines: QA experience with ETL/ELT workflows or data migrations
• Databases: Strong SQL skills; experience with Snowflake, SQL Server, Oracle, or MySQL
• Data Modeling: Solid understanding of relational and dimensional (star) schemas
• Programming: Python scripting for writing test cases

Nice To Haves

• Cloud Platforms: AWS, Azure, or Google Cloud
• Data Architectures: Data Lakes, AWS S3
• Data Logging: Splunk
• Orchestration & Integration: Matillion
• Data Formats & Scripting: JSON, XML, YAML, TypeScript, Linux shell scripting
• Additional Databases: Redshift, Aurora, DynamoDB, PostgreSQL, Redis
• Data Processing & Streaming: Snowpipes, Spark, Spark Streaming, Kafka, Kinesis, Pandas, Airflow
• AWS & DevOps: EC2, ECS, Lambda, Step Functions, EKS, EMR, Docker, CloudFormation, CDK

Responsibilities

• Design, develop, test, and maintain automation-first, scalable, and reliable data QA and validation processes
• Implement testing practices, integrating data quality checks early in pipeline design and development
• Validate data accuracy, completeness, and consistency across complex, high-volume datasets from multiple internal and external sources
• Analyze and interpret entity-relationship diagrams, relational models, and dimensional (star/snowflake) schemas
• Write, review, and optimize complex SQL queries in Snowflake (or equivalent platforms)
• Create and execute detailed test cases based on business and technical requirements, including interpretation of data mapping documents
• Define and document test strategies, test plans, and test summary reports
• Partner closely with Data Engineers and BI teams to clarify requirements, provide actionable feedback, and communicate testing results
• Build and maintain reusable regression testing frameworks to continuously ensure data quality across evolving pipelines
• Mentor team members and influence best practices for data testing, automation, and quality standards across the data engineering organization
• Proactively identify data quality risks and recommend improvements to pipeline design, testing approaches, and tooling

Benefits

• Full Coverage – Medical, Vision, and Dental
• Annual discretionary bonus and merit increase
• Work/Life Balance – generous sick days, vacation days, holidays, and wellness days
• 401(k) company matching
• Tuition Reimbursement (up to graduate degree)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level