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Jellyfish

Senior Software Engineer, Data Products

Posted 12 Days Ago
Remote or Hybrid
Hiring Remotely in United States
165K-235K Annually
Senior level
Remote or Hybrid
Hiring Remotely in United States
165K-235K Annually
Senior level
Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.
The summary above was generated by AI

Jellyfish is the backbone for elite engineering organizations, and we are looking for a Senior Software Engineer to join our team and turn our rich data into high impact features that solve real problems for our customers. You’ll leverage existing platform capabilities while acting as a critical internal customer, providing feedback that shapes the roadmap of our core data platform. If you are passionate about data storytelling, building performant user-facing data products, and collaborating with platform teams to unlock new capabilities, you’re the perfect fit.

What You’ll Actually Be Doing:

  • You’ll join a small, highly collaborative team that works together to define questions for user research, experiment with internal data, and produce prototypes to validate ideas. You’ll engage with internal and external users, and have the opportunity to engage in all phases of product development.

  • Your work will primarily involve Python, Databricks, and Postgres, with occasional excursions into SQL. You’ll develop deep knowledge of the data in our catalogue, and help set priorities for new data sources. You’ll partner with a data scientist and another software engineer to try out data transformations that result in insightful and useful metrics.

  • You’ll work closely with our platform teams as they build the pipelines, components, and APIs we’ll rely on. You’ll write requirements docs and proposals, and engage in synchronous collaboration with the teams building our core data pipelines. You care about being a thoughtful and communicative partner for the platform teams.

You’re a great fit:
  • Product-Minded Data Engineer – You have solid, hands-on production experience with Python, SQL, and data transformation concepts. You are comfortable working in Postgres and in modern data warehouses, ideally Databricks.

  • Cross-Functional Collaborator – You thrive on cross-functional teams, with access to user research, and think critically about solving problems. You identify quick ways to test hypotheses and break apart complex projects into manageable pieces.

  • Internal Platform Advocacy – You act as an internal customer for our platform teams, providing high-quality feedback that shapes the roadmap and improves the overall product ecosystem.

  • AI Native Engineer – You use AI tools effectively, and you’re eager to experiment with new ways of working. You’ll use our tools to evaluate those changes, improving both our workflows and our measurement tools.

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 is the leading intelligence platform for AI-Integrated engineering, helping more than 1,000 companies including DraftKings, Keller Williams and Blue Yonder, leverage AI to transform how they build software. By combining the industry’s deepest engineering dataset with context-rich intelligence, Jellyfish helps R&D organizations understand what’s driving impact, adopt proven industry best practices, and make smarter decisions across AI adoption, planning, delivery, and engineering performance.

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