Sr. QA Engineer

Job Description

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

Starz is an equal employment opportunity employer. All employees and applicants are evaluated on the basis of their qualifications, consistent with applicable state and federal laws. In addition, Starz will provide reasonable accommodations for qualified individuals with disabilities. Starz will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable state and federal law.