Senior Data & ML Engineer at Fiserv
Alpharetta, GA
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Jul 22, 2026
Alpharetta, GA
Jul 23, 2026
What this job asks for AI summary
A senior engineering role focused on building and maintaining data pipelines, ETL workflows, and MLOps infrastructure for a merchant analytics and offer recommendation platform within a digital onboarding team. Day-to-day work involves designing production-grade feature pipelines, integrating machine learning model outputs into live systems, and collaborating with data scientists and backend engineers to operationalize customer insights and personalization capabilities at enterprise scale. Suits an experienced data or ML engineer comfortable leading technical decisions across cloud-based, business-critical data platforms.
Senior level · 8+ years · 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
Rare in this occupation — lead with these, and say what you built with them.
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).
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)
The role is explicitly on-site Monday through Friday; no remote work is offered. The posting excludes candidates in Colorado, California, DC, Hawaii, Illinois, Massachusetts, Maryland, Minnesota, New Jersey, New York, Nevada, Rhode Island, Vermont, Virginia, Maine, and Washington — but does not name a specific city or metro, so no CBSA could be determined.
SOC classification is Medium confidence: the role spans data engineering (pipeline/ETL/warehouse — 15-1243) and ML engineering/MLOps (15-2051). The primary day-to-day emphasis on building scalable data pipelines, ETL workflows, and data services tips toward 15-1243, with 15-2051 as a genuine runner-up given the substantial ML/MLOps scope.
The AWS services list (S3, Glue, Lambda, SageMaker, CloudWatch, Step Functions, ECS/EKS) is presented as a single 'experience with' requirement in the required section; all are marked required. ECS and EKS are listed as interchangeable alternatives.
Feature engineering appears in the required section under 'supporting production ML workflows'; it is retained as a concrete ML capability gate rather than a generic concept.
The degree requirement states 'Bachelor's degree … or equivalent industry experience,' which means equivalent experience is accepted — the degree requirement is set to None.
Items under 'Experience That Would Be Great to Have' (CDC/streaming, feature stores, model registries, MLOps platforms, AWS certifications, Agentic SDLC, fintech domain experience) are all marked preferred.
No compensation figures are provided in the posting.
Read the full posting
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