Senior Python Engineer, DataFeed Team
Fliff · Europe (European Time Zone Based Candidate)
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Jul 19, 2026
Europe (European Time Zone Based Candidate)
Jul 21, 2026
What this job asks for AI summary
A senior Python engineering role on a sports data ingestion team, responsible for building and maintaining services that pull in data from external sports data providers, normalize and validate it, and distribute it across the platform. The work centers on near-real-time and batch pipelines, domain modeling for sports entities like events, markets, and odds, and improving observability and reliability when upstream feeds behave inconsistently. Suits an experienced backend engineer comfortable with Kafka, PostgreSQL, and async Python in production.
Senior level · 5+ years · Philadelphia-Camden-Wilmington, PA-NJ-DE-MD · Full-time
Posted 4 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
Roughly 180 people in the Philadelphia-Camden-Wilmington, PA-NJ-DE-MD area plausibly meet what this posting asks for (software developers). range 95–240
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
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 $135,966 (middle half $106,205–$168,771).
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)
The posting lists offices in Philadelphia, New York, Austin, and Sofia, Bulgaria. The primary HQ is Philadelphia; the role does not appear to be fully remote, though the JD does not explicitly restrict to one office location.
Django and Kafka appear in both the required section ('What We're Looking For') and the Nice To Have section. They are treated as hard gates based on their placement in the primary requirements block; the Nice To Have mention is a secondary reinforcement.
Terraform is inferred as the infrastructure-as-code tool from the Nice To Have mention of 'infrastructure-as-code experience' — no specific tool is named, so this is captured as preferred with Terraform as the canonical representative.
No compensation range is disclosed in the posting.
Read the full posting
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