Senior Data Warehouse Engineer

Company Summary: EchoStar 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. Department Summary: 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. Job Duties and Responsibilities: Candidates must be willing to participate in at least one in-person interview. This role addresses the complex challenges of scaling enterprise data infrastructure and maintaining peak system reliability across massive ecosystems. The position focuses on eliminating performance bottlenecks, streamlining ETL/ELT workflows, and maintaining strict data quality standards. Additionally, modernizing data pipeline engineering with cloud-native architectures and leveraging artificial intelligence will drive continuous operational excellence. What Success Looks Like (Objectives): Monitor and provide expert-level operational support for large enterprise data ecosystems using Snowflake and Databricks while resolving ETL/ELT bottlenecks Architect, maintain, and optimize scalable batch and streaming pipelines on AWS using clean, production-grade Python code Design, automate, and manage complex enterprise data workflows and job schedules using Apache Airflow and Control-M Champion Infrastructure-as-Code (IaC), manage CI/CD pipelines via GitLab, and integrate Generative AI tools like Amazon Q to drive operational efficiency Lead incident management, root cause analysis meetings, and operational metrics development to continuously improve production systems Collaborate within Agile/Scrum frameworks alongside Data Scientists, Analysts, and DevOps teams to execute complex data transformation logic Skills, Experience and Requirements: Core Skills and Competencies (What you’ll bring): Critical experience designing, developing, and engineering large-scale Enterprise Data Warehouses (EDW) and modern data lake architectures Advanced proficiency in SQL, Python, and Shell scripting for building and deploying production-grade data pipelines Deep expertise in AWS data services and cloud infrastructure, including IAM, VPC, CloudWatch, Redshift, and S3 Strong ability in relational and analytical data modeling utilizing Dimensional (Kimball) and 3NF structures High proficiency in DevOps best practices, version control using Git/GitLab, and IaC tools such as Terraform or AWS CloudFormation AI Literacy and Application skills to evaluate modern technologies like Generative AI tools (Amazon Q, Gemini, Databricks Genie Rooms) to accelerate development workflows Minimum Requirements: Minimum Education: Bachelor’s degree in Computer Science, Software Engineering, or a related technical field Minimum Experience: 4+ years of professional experience in Enterprise Data Warehousing and data lake engineering Required Technical Skills: Must have at least 3 years of experience with: SQL, Python, and Shell scripting AWS Cloud Data Platform (S3, Redshift, EC2, Glue), Snowflake or Databricks ecosystems Visa sponsorship not available for this role #LI-CH2 Benefits: We offer meaningful health perks, including flexible spending accounts, HSA, a 401(k) plan with company match, employee stock purchase plan, career opportunities, and a flexible time away plan. Review a benefits summary here: EchoStar 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. Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV ch…

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