Senior Analytics Engineer

Let’s talk about the Role

We’re looking for a Lead Analytics Engineer to empower Jellyfish to make high-velocity, data-driven decisions by building robust data pipelines, enabling self-serve analytics, and pioneering the context engineering required for modern AI and agentic workflows. We are rapidly implementing data systems to unlock AI-driven analytics workflows, and we’re looking for builders eager to make an impact. You’ll work closely with a wide range of stakeholders, primarily in Product, to solve business problems across Jellyfish. The breadth and complexity of available data continues to grow as we integrate more customer data streams (e.g. agent and token usage from Claude, Codex and Augment) and build more innovative products for our customers.

Most importantly, you’ll be part of a highly talented team working in a fun, challenging, and collaborative environment, building a fast-growing business led by experienced entrepreneurs and backed by top-tier investment partners.

Let’s talk about responsibilities:

• Partner with Product Teams: Collaborate with PMs to understand their business problems and then own the end-to-end data lifecycle to help solve them

• Event Data Architecture: Own the end-to-end event data lifecycle, including instrumentation, taxonomy design, and transformation pipelines.

• Pipeline Governance: Help build a DRY, modular data warehouse in our new Databricks database that prevents sprawl as AI makes code generation trivial.

• Self-Serve Enablement: Support product teams to independently answer questions using interfaces like Amplitude and Claude Code.

• Context Engineering: Structure a Single Source of Truth (SST) optimized for both human consumption and AI/agentic systems.

• Workflow Integration: Route high-quality product data into downstream tools beyond the Product team tools like Hex, Glean, Gainsight, etc.

• Flexible and Ready to Learn: Increase your impact by continuously learning and evolving your workflows as AI technology matures. Form opinions that help Jellyfish support its customers in their AI journeys.

Let’s talk about what you need to excel:

• Expertise in SQL and Python

• Experience with data warehousing concepts, cloud warehouses and BI tools

• Experience with dimensional modeling, semantic layers, and data quality best practices

• Experience with using data to tell a story and influence business decisions

• Proven ability to influence and ship with product and engineering teams, especially in B2B SaaS environment

• Strong perspective on using the appropriate data solution for the business need at hand and scaling product analytics solutions across a company.

• Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

• Tool-agnostic, highly flexible, and eager to continually reinvent data workflows to stay ahead of the AI curve.

A list of job experiences and qualification requirements is great, but humility, a performance-driven attitude, and a team-player approach are most important to us. We love to have fun and win in the process. We only hire people who have a passion for building great companies in an environment where a sense of humor is a must.

Occasional travel may be required.

Applicants must be authorized to work for any employer in the US. We are unable to sponsor or take over sponsorship of an employment visa at this time.

Let’s talk about us!
This is all about you, but you want to know a little about us. Jellyfish enables leaders to effectively build AI-integrated engineering teams, align engineering decisions with business initiatives and deliver the right software efficiently and on time. AI tools alone won’t transform your org—Jellyfish shows you what’s working, what’s not, and how to build high-performing teams that know how to use AI the right way.