Data Engineer
Excel Sports Management · Chicago, IL
$100,000–$115,000from the description
Jul 15, 2026
Chicago, IL
Jul 21, 2026
What this job asks for AI summary
An early-career data engineering role focused on building and maintaining data pipelines, automated testing, and data quality checks that support internal reporting, modeling, and client work. The position involves Python-based workflows, relational and columnar database design, schema migrations, and contributions to cloud infrastructure (primarily AWS) and CI/CD processes. It suits someone with around two years of data or software engineering experience who is comfortable working alongside analysts and senior engineers.
Mid level · 2+ years · Chicago-Naperville-Elgin, IL-IN-WI · 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
Roughly 25 people in the Chicago-Naperville-Elgin, IL-IN-WI area plausibly meet what this posting asks for (database architects). range 15–40
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $150,733 (middle half $127,994–$171,827). 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 (8)
The role is titled simply 'Data Engineer' with no level modifier; advertised seniority is Unspecified. The 2+ years requirement and framing as 'early-career' support a Mid-level classification.
A four-year degree is listed as 'OR equivalent experience,' so no hard degree gate exists.
S3, Athena/Glue, and PostgreSQL/Aurora appear in the responsibilities section as the team's stack context, but they are also directly tied to required duties ('Support the data lake and warehouse layer'), so they are treated as hard gates alongside the explicitly required qualifications.
Docker appears in the responsibilities section ('containerized (Docker) workflows') as a required duty rather than a nice-to-have, so it is treated as a hard gate.
LLMs/Generative AI is listed under Required Qualifications as 'Exposure to AI/ML or Generative AI/LLM-driven solutions' — a relatively low bar, but it is in the required section.
pytest is named as an example under the testing requirement ('e.g., pytest, schema/row-level checks, or similar'); the testing commitment itself is a hard gate, and pytest is the only named tool, so it is captured as required with the understanding that equivalent tools are acceptable.
The Knowledge, Skills and Abilities section (Apache Airflow, Terraform, Lambda, FastAPI/Flask, Power BI/Tableau) reads as a preferred/nice-to-have block and is marked accordingly.
The role is explicitly office-based in Chicago and is not eligible for visa sponsorship.
Read the full posting
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