Analytics Engineer

Sword Health is shifting healthcare from human-first to AI-first through its AI Care platform, making world-class healthcare available anytime, anywhere, while significantly reducing costs for payers, self-insured employers, national health systems, and other healthcare organizations. Sword began by reinventing pain care with AI at its core, and has since expanded into women’s health, movement health, and more recently mental health. Since 2020, more than 700,000 members across three continents have completed 10 million AI sessions, helping Sword's 1,000+ enterprise clients avoid over $1 billion in unnecessary healthcare costs. Backed by 42 clinical studies and over 44 patents, Sword Health has raised more than $500 million from leading investors, including Khosla Ventures, General Catalyst, Transformation Capital, and Founders Fund. Learn more at www.swordhealth.com. Analytics Engineer — AI Data Foundations Own the modeling, quality, and semantic layer that makes company data AI-ready. Your work lets our internal assistants reliably answer questions and power safe actions from trusted, fresh data. Internal AI Solutions We build AI tools that improve internal decision-making and productivity. You’ll work hand-in-hand with the Data team to structure high-value domains into AI-safe models, and with AI Engineers to deploy them into assistants, dashboards, and automations. What you’ll be doing:

Model core business domains into clear, documented star schemas (facts/dimensions) with stable names, units, and time grains.

Design an LLM-friendly semantic layer (synonyms, metric definitions, query guardrails, row/column-level policies).

Publish AI-safe consumption views/endpoints that enable constrained text-to-SQL with citations and data timestamps.

Data quality & observability: add tests/monitors, anomaly alerts, and cost/freshness dashboards.

Use Python to automate data quality checks, trigger alerts, or integrate new data sources into the modeling pipeline.

Contribute to workflow automation by connecting your data products with internal agents and actions, using modern scripting or low-code tools.

Partner & prioritize with stakeholders to unlock high-value internal questions and safe action workflows.

Document & enablement: concise glossaries and examples for analysts and AI consumers.

What you need to have:

3+ years of experience in analytics/data engineering, preferably in high-growth environments.

Strong command of SQL and experience building clean, tested, and well-documented data models (star/snowflake schemas).

Solid understanding of data modeling best practices, semantic layers, and version control.

Proficiency in Python for data tasks, especially scripting, testing, and API integrations.

Familiarity with concepts of AI-safe data modeling (e.g., naming consistency, freshness metadata, guardrails).

Curiosity and comfort working across data, product, and engineering teams.

Excellent written communication, you’ll write for humans and machines.

You should know how to use AI tools and techniques to enhance your daily productivity and decision-making.

What we would love to see:

Experience enabling AI assistants, agents, or chat-based interfaces with structured data sources.

Exposure to LLM-based systems (e.g., text-to-SQL, RAG pipelines) and the data prep they require.

Experience integrating data pipelines with automation platforms (e.g., orchestrators, webhook triggers, workflow runners).

Interest in building internal products that solve real business problems, and continuously iterating on them.

A mindset of trust, stewardship, and safety when handling and exposing internal data.

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.