Data Engineer II - AI Products

Company Summary

Echo Star is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV.

Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow.

Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.

Key Responsibilities:

• Design, implement, and optimize scalable, secure data pipelines using Databricks, Spark, and Delta Lake
• Build robust ingestion, transformation, and CI/CD workflows with Git Lab, ensuring performance, reliability, and cost-efficiency
• Apply software engineering best practices (SOLID, modular design, version control) to data workflows
• Develop unit tests, reusable testing frameworks, and enforce code quality through reviews and mentorship
• Refactor and maintain existing codebases for scalability, stability, and performance
• Collaborate with cross-functional teams and contribute to Agile ceremonies, shared libraries, documentation, and infrastructure standards supporting our AI Office

Education & Experience:

• Bachelor’s degree in Computer Science, Information Systems, or related field (Master’s preferred)
• 1-4+ years of data engineering experience building large-scale pipelines with Python, Databricks, Spark, and Delta Lake

Skills and

Qualifications:

• Proficient in Python (required) and Scala, with experience writing clean, testable, and modular code
• Strong understanding of data engineering principles, distributed systems, and modern data architecture
• Skilled in CI/CD practices, Dev Ops workflows, and automation of data pipeline deployments
• Experienced with unit testing (e.g., pytest) and ensuring data quality and pipeline reliability
• Familiar with AWS, containerization (Docker), and orchestration tools (ECS, EKS, Kubernetes)
• Strong communication, problem-solving, and collaboration skills; prior experience handling sensitive data is a plus
• Proven ability to apply SOLID principles, design patterns, and best practices to data solutions
• Experience with ML/NLP frameworks and infrastructure-as-code tools (Terraform, CDK, Cloud Formation) a plus

Visa sponsorship not available for this role

Compensation: $83,160.00/Year - $/Year

We offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: DISH Benefits.

The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location.

Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check. Our company is committed to fostering an inclusive and equitable workplace where every individual has the opportunity to succeed. We are dedicated to providing individuals with criminal or arrest records a fair chance of employment in accordance with local, state, and federal laws.

The posting will be active for a minimum of 3 days. The active posting will continue to extend by 3 days until the position is filled.

We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Echo Star will accommodate the sincerely held religious beliefs of employees if such accommodations are not undue hardships and are otherwise within the bounds of applicable law.

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