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# Data Warehouse Engineer

- **Company:** ECHOSTAR
- **Location:** Englewood, CO, United States
- **Experience:** Expert
- **Salary:** $96,000.0 - $138,000.0
- **Contract:** Permanent contract
- **Skills:** Third Normal Form, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Cloud Computing, Cloud Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Warehousing, DevOps, Identity and Access Management, Python (Programming Language), Scrum Methodology, Shell Script, Software Engineering, SQL Databases, Enterprise Data Management, Snowflake, Reliability of Systems, Generative AI, Amazon Virtual Private Cloud (VPC), Gitlab, Git, Cloudformation, Data Lakes, Infrastructure Automation Frameworks, Information Technology, AWS Data Analytics, Cloudwatch, Terraform, Data Pipelines, Amazon Redshift, Databricks, Control M
- **Published:** October 17, 2026
- **Apply:** https://www.builtincolorado.com/job/senior-data-warehouse-engineer/11731243?handler=ApplyRedirect

## About the Role

* 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 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

## Description

Build and optimize enterprise data warehouses, data lakes, and scalable batch and streaming pipelines. Support Snowflake and Databricks ecosystems, resolve ETL/ELT bottlenecks, automate workflows with Airflow and Control-M, and manage AWS-based infrastructure. Develop production-grade Python, SQL, and shell solutions while applying DevOps, CI/CD, IaC, and data modeling practices. Lead incident management, root cause analysis, operational metrics, and Agile collaboration with data and platform teams.
The summary above was generated by AI
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, 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)
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