Senior Data Engineer

AI Proficiency at Sword Health

AI fluency is a core expectation at Sword Health. Every candidate is assessed against our three-level framework — be ready to share real examples of how AI is already part of how you work.

Explorer (Level 1) — Uses AI daily to boost personal productivity

Builder (Level 2) — Creates workflows and tools that elevate the whole team

Integrator (Level 3) — Embeds AI into products and processes at scale

Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.

What you’ll be doing:

Design and operate the batch pipelines that power Sword’s warehouse and reporting — analytics, product, commercial, and clinical teams depend on what you ship.

Model data for analytics at scale: dimensional modeling, semantic layers, metric definitions that hold up across many stakeholders.

Own the transformation layer and make it something downstream users enjoy building on.

Build the curated, trusted datasets the rest of the business consumes — from source systems all the way through to the warehouse serving layer.

Support analysts, PMs, and clinical researchers in adopting warehouse data by raising the level of abstraction, not by writing their queries.

Contribute to lineage, governance, and documentation so what you model is discoverable and trusted.

Build and maintain AI-ready data infrastructure that feeds ML and AI products.

Leverage AI coding assistants and LLMs to accelerate development, automate documentation, and raise pipeline quality.

What you need to have:

Strong experience building batch pipelines and analytics datasets at scale.

Proficiency with Python and SQL - SQL especially; this role leans analytics.

Deep data modeling skills: dimensional, Data Vault, or similar; semantic layer design; metric definitions.

dbt in production as a first-class skill - you know how to structure a large dbt project, design for testability, and keep it maintainable as it grows.

Hands-on experience with at least one modern warehouse or lakehouse engine - Snowflake, BigQuery, Databricks, or Trino/Starburst.

Production experience with a workflow orchestrator (Airflow, Dagster, or similar).

Clear communicator: you can talk to PMs, analysts, and clinicians without drowning them in jargon.

Pragmatic: you ship the 80% solution and iterate.

Ownership: you don’t hand off broken pipelines.

Bonus

Familiarity with lakehouse table formats (Iceberg, Delta, Hudi).

Understanding of Kafka and event-driven sources, enough to consume them into batch layers sensibly.

Streaming exposure - Flink or Spark Structured Streaming - for when batch isn’t enough.

Experience with reverse-ETL, metrics stores, or semantic layer tooling (Cube, LookML, MetricFlow).

Experience in healthcare, HIPAA, or FedRAMP environments.

PySpark or Spark SQL at scale.

To ensure you feel good solving a big Human problem, we offer:

A stimulating, fast-paced environment with lots of room for creativity.

A bright future at a promising high-tech startup company.

Career development and growth, with a competitive salary.

The opportunity to work with a talented team and to add real value to an innovative solution with the potential to change the future of healthcare.

A flexible environment where you can control your hours (remotely) with unlimited vacation.

Access to our health and well-being program (digital therapist sessions).

Remote or Hybrid work policy.

To get to know more about our Tech Stack, check here .