Analytics Engineer
AI in this role
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 role:
We’re looking for an Analytics Engineer to join the team. 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.
What you will do:
Work with and expand on our foundational data stack — Looker, dbt, BigQuery, Airbyte
Write LookML and dbt models that describe our business, powering a self-serve analytics experience
Connect data from different sources (Salesforce, Stripe, Metronome, Clickhouse, 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 a deep understanding of our business metrics to drive alignment, prioritization, and decision-making
What you'll bring:
Have 3+ years experience in analytics engineering
Have technical proficiency in BigQuery (or similar), dbt, Looker/ LookML, Airbyte (or similar), Segment
Detail oriented, enjoys data spelunking, and can synthesize findings effectively
Bring curiosity and a strong business sense to help anticipate needs and generate meaningful insights
Start-up DNA with the ability fast-paced and unstructured environments
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-$175,000
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
How we rate this
Analytics Engineer at LangChain rates 24 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used LangGraph in your day-to-day work.
- What are the limits of Clay that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: AI Agents, LangGraph, and Clay. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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