Data Engineer
Reply · Chicago, IL
$85,000–$100,000from the description
Jul 22, 2026
Chicago, IL
Jul 23, 2026
What this job asks for AI summary
A data engineering role focused on building and maintaining data pipelines, ETL workflows, and data migration initiatives within an IoT and cloud computing consultancy. The work also involves collaborating with data scientists to support machine learning models and AI-driven applications. Suited to someone with solid Python experience, familiarity with AWS or Azure, and hands-on ETL and Databricks background.
Mid level · 3+ years · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
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 (6)
Location is not specified in the posting; no CBSA or state could be determined. The role may be remote or at an unspecified US office — the talent acquisition team should clarify.
US citizenship or green card holder is a hard client requirement stated in Minimum Requirements.
AWS and Azure are listed together as interchangeable cloud platform options ('AWS or Azure'); AWS is listed as the primary with Azure as the alternative.
ETL frameworks are mentioned alongside ETL pipeline experience but no specific framework is named, so only the general ETL pipelines skill is captured.
CI/CD pipeline development appears under Preferred Qualifications and is marked accordingly.
The role sits at the intersection of data engineering (pipelines, ETL, Databricks) and ML/AI work (building ML models, AI-driven applications). Data pipeline/platform building is the primary framing, so 15-1243 (Database Architects) is the primary SOC, with 15-2051 (Data Scientists) as a plausible runner-up given the ML/AI responsibilities.
Read the full posting
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