Software Engineer III – Data

Job not on LinkedIn

🕒 September 7

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 20%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Fanatics Betting & Gaming

WebsiteAll Job Openings

- employees

🎲 Gambling

⚽ Sports

👥 B2C

Gambling • Sports • B2C

Fanatics Betting & Gaming is a consumer-facing U. S. sports betting and online casino operator (branded as Fanatics Sports & Casino / Fanatics Sportsbook / Fanatics Casino) that offers sportsbook betting, online casino games, event contract trading (Fanatics Markets), and a unified loyalty currency called FanCash. It provides mobile apps and web experiences, state-by-state availability across many U. S. jurisdictions, promotional offers, partnerships with sports teams, and responsible-gaming tools and disclosures. Morton St. Trading Investments, LLC handles the event-contract trading side and is CFTC-registered.

📋 Description

• Implement new ingestion sources end-to-end against a senior engineer's design, including connector code, DAG, schema, monitoring, and catalog registration • Extend the team's existing ingestion framework where a new source needs an unsupported pattern • Investigate pipeline failures independently, recognize known issue classes, and ship documented fixes • Identify downstream consumers and risks before shipping new pipelines, and flag gaps during specification review • Write clear handovers when escalating unresolved issues • Review peers' pipeline pull requests and catch non-obvious issues such as missing idempotency checks and race conditions • Turn ambiguous data-quality questions into structured investigations by tracing data lineage from source to warehouse • Surface concerns in specification reviews as specific, well-reasoned questions • Support data security and governance work, including PII masking and access controls • Contribute to data delivery work, including reverse ETL integrations • Build relationships with internal stakeholders and help scope and clarify requirements • Mentor DE2s on significant projects and help them apply team conventions

🎯 Requirements

• 3–5 years of professional software or data engineering experience • Strong SQL and Python skills, with solid experience building and operating production data pipelines • Comfort investigating and root-causing pipeline issues independently before escalating • Experience with workflow orchestration tools (Airflow or similar) and a cloud data warehouse/lakehouse (Snowflake, Databricks, or similar) • Solid understanding of data pipeline concepts: idempotency, schema evolution, backfills, and data quality/testing • Experience giving substantive code review feedback, not just style or formatting comments • Strong communication skills — can write a clear technical handover, ask sharp questions in spec review, and explain a data lineage investigation to a non-technical stakeholder • A track record of taking ownership of known-class problems end-to-end rather than needing step-by-step direction • Experience extending or building reusable pipeline frameworks/templates • Exposure to reverse ETL tools or patterns, PII masking, or data access governance (RBAC) • Exposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting • Some experience mentoring or informally supporting more junior engineers • Background in gaming, betting, e-commerce, or another regulated/high-compliance industry

🏖️ Benefits

• Real ownership over known-class problems, with senior/staff support available for the genuinely novel ones • Work on high-visibility, high-trust systems that the business depends on • A culture built around clear tenets: standardize before you scale, own the outcome (not just the ticket), and clarity over complexity • Clear growth path into Senior Data Engineer, with room to start mentoring and shaping team practices along the way

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