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
Education / Work Experience 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)
Required Skills
- 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 Have Skills
- 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
Compensation
$125,000 - $145,000
About STARZ
STARZ (NASDAQ: STRZ) is the leading premium entertainment destination for women and underrepresented audiences, and home to some of the most popular franchises and series on television. STARZ offers a robust programming mix for discerning adult audiences, including boundary-breaking originals and an expansive lineup of blockbuster movies, and is embodied by its brand positioning “We’re All Adults Here.” Complementary to any platform or service, STARZ is available across a wide range of digital OTT platforms and multichannel video distributors and is a bundling partner of choice. STARZ is powered by an industry-leading advanced technology, data analytics and digital infrastructure and the highly rated and first-of-its-kind STARZ app.
Our 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)
EEO Statement