Agentic Data Engineer II

EchoStar is building and scaling data infrastructure to support modern analytics and emerging AI initiatives. In this onsite role in Littleton, CO, you will develop production-grade data pipelines and workflows designed for machine learning and large language model (LLM) consumption, with an emphasis on observability, governance, and cost-aware operations.

You will also work on LLM feature store and AI application workflows, including automated monitoring and self-healing mechanisms to keep systems reliable in production.

What you’ll do

• Design scalable data pipeline solutions that optimize current infrastructure performance and improve resource utilization
• Use cost-effective engineering practices to prioritize work that improves operational efficiency and data deliverability
• Build and maintain reliable pipelines for LLM feature stores and AI application workflows
• Create automated monitoring and self-healing mechanisms to detect workflow failures and trigger corrective actions
• Integrate observability tooling to track data freshness, lineage, and baseline performance metrics across production environments
• Model and structure complex datasets into standard semantic layers to enable low-latency access for downstream AI systems and analytical queries
• Participate in at least one in-person interview

Required qualifications

• Practical experience developing and deploying production-grade data pipelines within cloud environments
• Experience evaluating technical stacks and optimizing existing data processing workflows before adding new tools
• Ability to build new AI Agents to support business operations
• Applied AI skills, including integrating large language models and vector datasets into enterprise data pipelines
• Strong proficiency in Python and SQL for data transformation, scripting, and API integration
• Solid skills with Git version control, containerization tools, and CI/CD deployment pipelines
• Proven troubleshooting skills to diagnose bottlenecks and resolve issues in distributed data platforms
• Education: Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a closely related technical field
• Education: Bachelor’s Degree in Computer Science or a related technical field
• Experience: 2 years of experience in data engineering
• At least 1 year of experience with Databricks, including Spark optimization and Delta Lake architecture
• At least 1 year of experience with Snowflake, including building and optimizing relational data models
• At least 1 year of experience with Python and SQL for data manipulation
• Visa sponsorship: Not available for this position

Technologies

• Python, SQL, Git, CI/CD
• Databricks, Spark, Delta Lake, Delta Lake architecture
• Snowflake
• LLM, vector datasets
• Containerization tools

Compensation

• Location: Littleton, CO (onsite)
• Salary range: USD 83,160 - 118,800 per year
• The base pay range shown is a guideline. Individual total compensation will vary based on qualifications, skill level, and competencies. Compensation is based on the role’s location and is subject to change based on work location.

Benefits

• Flexible spending accounts
• HSA
• A 401(k) Plan with company match
• ESPP
• Career opportunities
• A flexible time away plan