AI Data Engineer II at EchoStar
Denver, CO
$100,980–$136,625from the description
Jul 17, 2026
Denver, CO
Jul 21, 2026
What this job asks for AI summary
A data engineering role focused on designing and maintaining large-scale data pipelines using Databricks, Spark, and Delta Lake on AWS. The work involves building automated CI/CD workflows in GitLab, applying structured software engineering practices, and helping move data science models into stable production systems. Suited to engineers with at least three years of hands-on experience in Python, SQL, and AI/data platforms.
Mid level · 3+ years · National · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $142,568 (middle half $111,775–$173,013). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
No specific work location or metro area is stated in the posting; compensation is noted as location-dependent and subject to change based on work location, so the CBSA is left blank.
The role sits at the boundary between data/pipeline engineering (15-1243) and software development (15-1252); the strong emphasis on SOLID principles, modular design, testing frameworks, and CI/CD leans toward software engineering, but the primary deliverable is scalable data pipelines on Databricks/Spark, which tips toward data architecture.
The minimum experience requirement is 3+ years, which maps to Mid-level, despite the scope language (code reviews, mentoring, cross-functional leadership) that reads more Senior; the explicit minimum gates are used here.
Docker and Kubernetes appear together under 'Core Skills' as 'Docker or Kubernetes' — emitted as two separate preferred skills with each listed as an alternative for the other, since the JD treats them as interchangeable options rather than a combined stack requirement.
AWS is mentioned in the 'Core Skills' narrative section (not the hard-gated 'Required Technical Skills' block), so it is treated as preferred.
Machine learning libraries and NLP frameworks are referenced in the Core Skills section but no specific tools are named, so no skill entries are emitted for them.
Visa sponsorship is explicitly not available for this role.
Read the full posting
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