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Data Engineer

Key Facts

Remote From: 
Category:  Data Engineer
Full time
Senior (5-10 years)
English

Other Skills

  • •
    Problem Solving
  • •
    Collaboration
  • •
    Adaptability
  • •
    Curiosity

Roles & Responsibilities

  • 5+ years building production data systems and pipelines in Python or a comparable typed language
  • Strong SQL and data-modeling fundamentals; experience with a modern cloud warehouse (Snowflake, BigQuery, Redshift, or similar) and a transformation framework like dbt
  • Hands-on experience deploying machine-learning models to production, owning training, inference, evaluation, and rollout, not just notebooks
  • Familiarity with at least one transformer-based ML framework (PyTorch + Hugging Face Transformers preferred)

Requirements:

  • Design, build, and own the data pipelines and ML services that classify product eligibility and power downstream decisions across Flex
  • Model the data domain (products, merchants, eligibility rules, classifications, and outcomes) in warehouses and serving systems other teams build on
  • Partner with backend, product, and operations stakeholders translating merchant and consumer needs into reliable data products, models, and APIs
  • Own and improve the architecture of the data warehouse, transformation layer, ML training and inference systems, and real-time serving paths

Job description

About Flex

Flex addresses a critical problem: enabling health and wellness brands to accept HSA and FSA payments online. Backed by First Round, Core VC, and Rethink Capital, the company powers checkout for brands like Equinox, Dermstore, Therabody, and Ultrahuman. The platform verifies product eligibility in real time, manages split payments, and issues Letters of Medical Necessity at checkout. With $150 billion in annual HSA/FSA spending potential, Flex unlocks new revenue opportunities for merchants and simplifies benefit usage for consumers.

 
 

About the Role

The company seeks a Data Engineer to design and operate the data and machine-learning systems that determine HSA/FSA eligibility at scale: the pipelines, models, and APIs that turn raw merchant catalogs into structured, classified, decision-ready data at checkout. You'll partner with backend, product, and operations stakeholders to build the systems that move every eligibility decision Flex makes.

This role suits those thriving in ambiguity, taking initiative, and excited about building at an early-stage company.

 
 

Responsibilities (What You'll Do)

  • Design, build, and own the data pipelines and ML services that classify product eligibility and power downstream decisions across Flex

  • Model the data domain (products, merchants, eligibility rules, classifications, and outcomes) in warehouses and serving systems other teams build on

  • Partner with backend, product, and operations stakeholders translating merchant and consumer needs into reliable data products, models, and APIs

  • Own and improve the architecture of the data warehouse, transformation layer, ML training and inference systems, and real-time serving paths

  • Analyze, troubleshoot, and resolve production issues rooted in data quality, model accuracy, pipeline reliability, and serving latency

  • Collaborate on cross-functional projects connecting the full Flex experience, from consumer checkout to merchant analytics

  • Build and maintain evaluation harnesses, golden datasets, and observability for the models and pipelines you ship

  • Create and maintain documentation for data models, pipelines, and on-call runbooks

  • Contribute to a culture of learning, problem-solving, and operational excellence

 
 

Qualifications (Who You Are)

  • 5+ years building production data systems and pipelines in Python or a comparable typed language

  • Strong SQL and data-modeling fundamentals; experience with a modern cloud warehouse (Snowflake, BigQuery, Redshift, or similar) and a transformation framework like dbt

  • Hands-on experience deploying machine-learning models to production, owning training, inference, evaluation, and rollout, not just notebooks

  • Familiarity with at least one transformer-based ML framework (PyTorch + Hugging Face Transformers preferred) and a working sense of when classical or embedding-based models beat LLMs and when they don't

  • Resourceful, curious, and comfortable learning new tools quickly

  • Thrive in fast-paced, dynamic environments and enjoy wearing multiple hats

  • Collaborative and enjoy working across teams to solve problems

  • Execution mindset with focus on end users

  • Proficient at leveraging AI tools to ship faster

 
 

Nice to Have

  • Experience with serverless compute platforms for data and ML workloads (Modal, Ray, AWS Lambda, GCP Cloud Run, or similar)

  • Production experience with vector databases and embedding-based retrieval

  • Self-hosted LLM inference experience (vLLM, TGI, SGLang) and a working sense of GPU economics

  • Background in payments, fintech, or health benefits (HSA/FSA), or another regulated, money-moving domain

  • Experience building or maintaining a golden-dataset evaluation harness for an ML system

  • Comfort reading and contributing to a Rust-based backend that consumes your APIs

 
 

Why Join Flex

  • A mission-driven team making healthcare spending effortless

  • Early-stage impact: your work directly shapes growth and success

  • Collaborative, high-trust, and transparent culture

  • Competitive compensation and equity package

  • Flexible, remote-friendly work environment

 
 

Compensation & Benefits

Salary: $160K to $220K

Equity: Offers Equity

Additional Benefits:

  • Medical, dental, and vision plans

  • Unlimited PTO and sick days

  • Paid parental leave

  • Flexible, remote-first environment

 
 

Equal Opportunity

Flex is an equal opportunity employer encouraging applicants from all backgrounds and life experiences. The company celebrates diversity and does not discriminate based on race, religion, color, national origin, sexual orientation, gender identity, gender expression, age, veteran status, disability status, or any other legally protected characteristic.

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