Inabia Software & Consulting Inc. · Columbus/Dallas/Atlanta

Salary
Posted
Jul 21, 2026
Location
Columbus/Dallas/Atlanta
Last confirmed open
Jul 22, 2026

What this job asks for AI summary

This role centers on building and maintaining end-to-end MLOps infrastructure on Databricks running on AWS. Day-to-day work involves automating ML workflows — from feature engineering and model training through deployment and monitoring — using tools such as MLflow, Databricks Model Serving, Delta Lake, and Terraform. It suits engineers with strong hands-on MLOps experience who are comfortable bridging data science and platform engineering teams.

Senior level

Must have (19)
DatabricksPythonPySparkSQLMLflowDatabricks Model ServingDatabricks WorkflowsDelta LakeAWS or EKSIAMLambdaECRSecrets ManagerGitBitbucketJenkinsDatabricks Asset BundlesTerraformUnity Catalog

“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

What gives you an edge
Unity Catalog2%Databricks Workflows3%Delta Lake5%IAM7%MLflow8%Terraform11%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python88%SQL72%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $122,874 (middle half $87,544–$162,374).

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 (4)

No employment type, compensation, or degree requirement is stated.

This role sits at the intersection of MLOps engineering and data science. The primary day-to-day work is operationalizing and productionizing ML models (MLflow, Databricks Model Serving, CI/CD pipelines, Terraform), which leans toward software/platform engineering (15-1252), but the ML lifecycle ownership — feature engineering, model monitoring, drift detection, retraining — anchors it in data science (15-2051). 15-2051 is chosen as primary; 15-1252 is a genuine runner-up.

ECS and EKS are listed together as 'ECS/EKS' in the posting, indicating either/or familiarity; captured as one skill with EKS as an alternative.

All skills are drawn from the explicit 'Required Skills' section and are therefore treated as hard gates.

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