Senior AI Platform Engineer
US-CO-Denver
Attract-careers1
Req #: 97732
Type: Fulltime-Regular
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Overview: 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. Responsibilities: Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session. EchoStar is seeking a Senior Databricks AI Enablement Engineer to lead the technical onboarding of users, teams, and data domains onto the enterprise Databricks platform. This role is responsible for connecting external data sources, enabling governed AI and ML use cases, supporting Databricks Genie and related AI capabilities, and ensuring new workloads are onboarded with the right tagging, cost attribution, access controls, and operational standards. This is a hands-on engineering role for someone who understands how to make Databricks usable at scale. The right candidate can connect source systems, structure data for analytics and AI, guide users on platform capabilities, and enforce the governance and financial controls needed for enterprise adoption. What Success Looks Like (Objectives) * Accelerate the technical onboarding of new users and business units by implementing standardized, scalable platform configurations * Architect seamless integrations for external enterprise data sources to enable high-impact analytics and governed AI use cases * Deploy Databricks-native AI capabilities, including Genie and Mosaic AI, to ensure innovative solutions are practical and supportable * Enforce enterprise-wide standards for metadata, Unity Catalog registration, and data lineage to maintain high data integrity * Establish transparent financial accountability through robust chargeback practices and usage-aligned cost allocation reporting * Design reusable automation templates and self-service patterns that reduce manual friction for onboarding common data products Qualifications: Core Skills and Competencies (What you'll bring) * Advanced technical expertise in the Databricks production ecosystem, specifically regarding Delta Lake and Unity Catalog architecture * Mastery of Python, SQL, and PySpark for designing resilient and sophisticated data engineering pipelines * Deep conceptual knowledge of AI Innovation, including the practical application of LLM-driven workflows and vector search patterns * Critical experience in cloud platform governance, focusing on security standards, access controls, and auditability within AWS * Professional aptitude for FinOps and platform cost management to ensure long-term financial sustainability of technical workloads * Strong collaborative communication abilities to translate complex technical requirements for both engineering teams and business stakeholders Additional Qualifications * Experience with LLM application design, including retrieval-augmented generation and agent frameworks. * Proficiency in CI/CD for Databricks deployments using Terraform, Asset Bundles, or GitLab * Active Databricks certifications in Data Engineering, Platform Administration, or Machine Learning Minimum Requirements * Minimum Education: Bachelor's Degree in Computer Science, Information Systems, Data Engineering, or a related technical field * Minimum Experience:5 years of experience in data engineering, platform engineering, or cloud data roles * Required Technical Skills: * Experience with 3+ years of hands-on Databricks production environment management * Proficiency in Python and PySpark for data pipeline design * Proven experience implementing Unity Catalog and governance controls at scale Visa sponsorship not available for this role
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