Senior Data Warehouse Engineer
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Oct 16, 2026.
What Success Looks Like (Objectives):
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
Core Skills, Competencies, and Key Experiences (What you’ll bring)
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
Salary Range
Compensation: $96,250.00/Year - $137,500.00/Year
About Our Department
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.
About Our Company
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.
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 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.
This job posting will be active for a minimum of 3 days and 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. EchoStar 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. All qualified applicants with arrest or conviction records will be considered for employment in accordance with local, state, and federal law. You may redact any information that identifies age, date of birth, or dates of school/graduation from your application documents before submission and throughout our application process.
EchoStar will provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities, unless doing so poses an undue hardship on the Company, poses a direct threat of substantial harm to others, or is otherwise not required by law. EchoStar has a more detailed Accommodation Policy that applies to employees. EchoStar endeavors to make echostar.com and jobs.echostar.com accessible to users. Please contact [email protected] if you would like to discuss the accessibility of our website or need assistance completing the application process. This contact information is for accommodation requests only; do not use this contact information to inquire about the status of applications. If you have questions regarding your application or the recruitment process please email [email protected].
Click the links to access the following statements: EEO Policy Statement, Pay Transparency, EEOC Know Your Rights (English /Spanish)
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
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