Jellyfish processes a huge amount of engineering data, and we are investing heavily in the foundations that make that data reliable, governable, and easy to use. We are looking for a Data Engineer to help mature our Databricks-based data platform, establish strong data modeling patterns, and build the systems that move data from raw ingestion to trusted production datasets.
You’ll work across ingestion, transformation, storage, governance, and serving. If you enjoy turning messy data pipelines into durable platform architecture and want to help define how a modern lakehouse should actually operate, you’re the perfect fit.
What you’ll actually be doing:
Databricks Platform Development - You’ll build and maintain data pipelines and datasets in Databricks and Delta Lake, improving reliability, performance, and operational visibility across the platform.
Medallion Architecture - You’ll help establish clear Bronze, Silver, and Gold layer responsibilities, including standards for schema evolution, transformation ownership, data retention, and promotion between layers.
Data Modeling - You’ll design durable canonical models for core Jellyfish entities and relationships. You’ll work with application and analytics teams to ensure downstream datasets are structured around consistent definitions rather than one-off transformations.
Pipeline Engineering - You’ll build and improve batch and incremental pipelines using technologies like Databricks, Airflow, Spark, and cloud object storage. You’ll focus on idempotency, scalability, observability, and recoverability.
Data Governance and Quality - You’ll work with our catalog and governance tooling to establish lineage, ownership, schema standards, quality checks, and discoverability across the platform.
Serving and Egress - You’ll help create reliable patterns for moving curated data from Databricks into systems like ClickHouse and other future serving destinations without tightly coupling the platform to any single database.
You’re a great fit if:
Databricks Experience - You’ve worked extensively with Databricks, Spark, Delta Lake, or a comparable lakehouse platform and understand how to operate it beyond simply writing notebooks.
Data Engineering Fundamentals - You understand partitioning, incremental processing, schema evolution, distributed execution, file formats, and the performance characteristics of large analytical datasets.
Strong Data Modeling Skills - You can reason about canonical entities, relationships, grain, dimensional modeling, and the boundary between platform models and consumer-specific models.
Pipeline Reliability Mindset - You design pipelines to be observable, retryable, idempotent, and understandable when they fail.
Cloud Fluency - You understand how object storage, compute, networking, IAM, and managed data services fit together in a modern cloud data architecture.
Pragmatic Platform Builder - You care about standards and architecture, but you also know when to ship a practical solution and iterate.
Bonus Points:
You’ve helped build or migrate to a medallion-style lakehouse architecture.
You’ve worked with Databricks Unity Catalog, OpenMetadata, or another governance and lineage platform.
You’ve implemented CDC pipelines from PostgreSQL, RDS, or Aurora.
You’ve worked with Airflow or another production workflow orchestration platform.
You’ve moved analytical data into serving systems like ClickHouse, Snowflake, BigQuery, or similar platforms.
You’ve helped introduce data contracts, canonical schemas, or platform-wide data quality standards.
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.
Skills Required
- Extensive experience with Databricks, Spark, Delta Lake, or a comparable lakehouse platform
- Understanding of partitioning, incremental processing, schema evolution, distributed execution, file formats, and large analytical dataset performance
- Strong data modeling skills, including canonical entities, relationships, grain, dimensional modeling, and platform versus consumer models
- Experience designing observable, retryable, idempotent, and recoverable data pipelines
- Understanding of cloud object storage, compute, networking, IAM, and managed data services
- Pragmatic platform-building and data architecture approach
- Experience with medallion-style lakehouse architecture
- Experience with Databricks Unity Catalog, OpenMetadata, or another governance and lineage platform
- Experience implementing CDC pipelines from PostgreSQL, RDS, or Aurora
- Experience with Airflow or another production workflow orchestration platform
- Experience moving analytical data into ClickHouse, Snowflake, BigQuery, or similar serving platforms
- Experience introducing data contracts, canonical schemas, or platform-wide data quality standards
- Authorization to work for any employer in the United States without sponsorship
Jellyfish Compensation & Benefits Highlights
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Healthcare Strength — Top-tier medical and dental plans are highlighted, with vision options, company‑paid short‑ and long‑term disability, and voluntary life, accident, critical illness, and hospital coverage. Mental‑health resources and inclusive care such as transgender healthcare and abortion‑travel support are also described.
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Leave & Time Off Breadth — Flexible Time Off (unlimited/discretionary) plus 13 company holidays are consistently advertised. Paid sick days and bereavement leave are also described in benefit overviews.
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Parental & Family Support — Paid parental leave and family medical leave are included, with signals like an onsite Mother’s Room and active parent communities. Company‑sponsored family events and ERGs further underscore family support.
Jellyfish Insights
What We Do
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.
Why Work With Us
Are you fueled by innovation and energized by challenges? At Jellyfish, every day is a chance to make an impact, and do the work that matters most. We solve meaningful challenges that shape how engineering organizations operate. We are committed to cultivating a Jellyverse where everyone can do their best work, creating a place where we all thrive.
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Jellyfish Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We are remote first with employees located throughout the US. Jellyfish does have a Boston office for those that wish to collaborate in person.









