Senior Data Engineer

Job not on LinkedIn

🕒 July 31

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

💵 $125k - $155k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 8%

What it means: how likely this posting is sitting open without active hiring.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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FutureFit AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 Seed Round on 2022-03

Artificial Intelligence • B2B • SaaS

FutureFit AI is a software development company that empowers workers with an AI-powered tool designed to serve as a GPS for career navigation. By partnering with Fortune 500 companies, governments, and workforce development organizations, FutureFit AI provides solutions that support career transitions, from upskilling and reskilling to job placement. Utilizing over 350 million global talent profiles and proprietary algorithms, the company offers personalized roadmaps for learning and career support, effectively harnessing data to optimize workforce development and planning.

📋 Description

• Design, build, and operate the ingestion and transformation pipelines that bring labor market, customer, and product data into our warehouse as well as into the product • Own how our core data is structured, tested, and documented, including the skills, occupation, and career taxonomies at the center of the product • Build the transformation layer and datasets that power internal analytics, Looker/Quicksight reporting, and the insights we deliver to customers • Build and maintain the pipelines that feed our matching and recommendation models, and partner with Engineering and Data Scientists to get models deployed, monitored, and improved in production.

🎯 Requirements

• Strong data engineering experience (roughly 4+ years) designing and operating production ETL/ELT pipelines that other people and systems depend on • Fluency in Python and SQL, with real depth in SQL — experience in modeling data in a warehouse/data lake, not simply querying it • Hands-on experience with a modern orchestration and transformation stack (Airflow, dbt, or close equivalents) and with cloud data warehouses • Experience integrating data from varied external sources — third-party data providers, APIs, flat file feeds — including handling schema changes, unreliable delivery, and inconsistent quality from upstream • Comfort working with large, messy, inconsistently structured data, and sound judgment about when to clean it, when to model around it, and when to push back on the source • A builder's instinct for reliability: testing, monitoring, and debugging your own pipelines rather than waiting for someone to report the breakage • Clear communication: you can explain a data model and its tradeoffs to a non-technical audience.

🏖️ Benefits

• Competitive salary • Flexible work arrangements • Professional development opportunities • Travel for team gatherings and off-sites