Analytics Engineer

LangChain

Boston (MA)

Hybrid

USD 140,000 - 180,000

Full time

14 days+

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Job summary

LangChain is expanding its data team and seeks an analytics engineer to build data infrastructure and deliver actionable insights. You will enable business teams to diagnose issues, spot opportunities, and drive success using data.

If you enjoy scalable data platforms and storytelling with data, this role is for you. Location options include SF, NYC, Boston, or Remote U.S., with a compensation package designed for impact and equity.

Qualifications

  • 3+ years experience in analytics engineering or data engineering
  • Proficiency in BigQuery, dbt, Hex, Fivetran and Segment
  • Detail oriented with ability to synthesize findings
  • Curiosity and strong business sense to derive insights
  • Start-up environment suitability and self-direction
  • Self-directed work style and ability to make an impact without constant oversight

Responsibilities

  • Build scalable dbt models and context describing business metrics
  • Expand and maintain the foundational data stack (Fivetran, dbt, BigQuery, Hex)
  • Ingest data from Salesforce, Stripe, Postgres, and more into BigQuery
  • Create dashboards tracking progress against company goals and KPIs
  • Analyze product usage and operational data to surface insights on health, adoption, revenue
  • Develop understanding of business metrics to drive alignment and decision making

Skills

Analytical mindset
Self-directed
Startup DNA
Detail-oriented

Tools

BigQuery
dbt
Hex
Fivetran
Segment

Job description

About Us

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

About the team:

We are a small but mighty team of three analytics engineers powering LangChain’s internal data infrastructure and analytics. We’re a full-stack team, meaning we work end-to-end across the data stack, from data ingestion to enabling self-serve agentic analytics. Learn more about what we’ve built so far here!

About the role:

We are expanding our data team and looking for a analytics engineer to join us. We build products used by elite companies and over a million developers, and data plays a critical role in sharping our strategies and decision making. In this role you will help lay the foundation for business teams to diagnose issues, uncover opportunities, and drive success using data. If you enjoy building data infrastructure and empowering teams with actionable insights, this role is for you.

*Location: SF, NYC, Boston, or Remote U.S.

What you will do:
  • Build scaleable dbt models and context that describe our business, powering a self-serve analytics experience

  • Work with and expand on our foundational data stack — Fivetran, dbt, BigQuery, Hex

  • Connect data from a variety of sources (Salesforce, Stripe, Metronome, Postgres, etc) into our BigQuery warehouse

  • Build dashboards that track progress against company goals and KPIs

  • Analyze product usage and operational data to surface insights around customer health, adoption, and revenue

  • Develop and leverage a deep understanding of our business metrics to drive alignment and decision-making

What you'll bring:
  • 3+ years experience in a related role (analytics engineer, data engineer, or similar)

  • Technical proficiency in BigQuery, dbt, Hex, Fivetran, Segment (or similar tools)

  • Detail oriented, enjoys data spelunking, and can synthesize findings effectively

  • Curiosity and a strong business sense to help anticipate needs and generate meaningful insights

  • Start up DNA. You thrive in fast-paced and unstructured environments and are energized by finding out what matters most

  • You are self-directed - you don’t wait for process or oversight to start making an impact

Compensation & Benefits:

We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations.

Annual salary range: $140,000-$180,000

Compensation Philosophy:

We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.

We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

Benefits

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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