Data Engineer

jellyfish· Engineering
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🌍 Remote📍 Remote - USFullTime💰 USD 165K–205K/yr

About this role

Jellyfish is the backbone for elite engineering organizations, and our data pipelines need to be as high-performing and reliable as the teams we serve. We are looking for a Data Engineer to join our data platform team and help us execute, automate, and maintain the next generation of our Jellyfish data platform. In this role, you’ll be a core builder—fully autonomous, highly proficient, and responsible for translating architectural blueprints into clean, production-grade pipelines. If you view manual data patches and unmonitored workflows as bugs to be squashed and want to write code that directly impacts how the world’s best engineering leaders measure their output, you’re the perfect fit.

What you’ll actually be doing:

  • Core Pipeline Engineering – You’ll write the clean, modular Python and optimized SQL that drives our daily data transformations. You will be responsible for implementing our Medallion-layer data models (Bronze → Silver → Gold), ensuring high performance and data integrity.

  • Modern Orchestration & Tuning – You’ll manage and tune our workflow orchestration engines (like Prefect or Dagster). You’ll hunt down slow execution paths, optimize parameter serialization (e.g., leveraging Pydantic v2), and ensure our distributed processing jobs run efficiently.

  • Infrastructure as Code (IaC) – You won't just write data scripts; you'll own your infrastructure deployment. You will use Terraform to manage and provision data warehouse schemas, permissions, and tables across securely isolated staging and production catalogs.

  • API & Caching Integration – You’ll collaborate with product developers to expose data safely. You’ll help implement and maintain the application backend tiers, backend-for-frontend (BFF) layers, and Redis caching structures that protect our core data warehouse from frontend concurrency spikes.

  • On-Call & Pipeline Observability – You’ll participate in our data platform's incident response rotation. When a pipeline breaks, you won't just fix the data; you’ll refine the Datadog dashboards and alerts to ensure we catch the issue earlier next time.

You’re a great fit if:

  • Data Engineering Fluency – You have solid, hands-on production experience with Python, advanced SQL, and data transformation concepts. You are comfortable building and scheduling workflows using programmatic orchestrators (such as Prefect, Dagster, or Airflow).

  • Warehouse & Catalog Practitioner – You know your way around enterprise data platforms (e.g., Snowflake, Databricks, BigQuery). You understand how to navigate environment boundaries, manage access keys securely, and write performant queries.

  • Automation Mindset – You look at a repeated data backfill, a manual schema fix, or an untracked data quality bug and immediately think about how to script a permanent, automated solution.

  • Collaborative Builder – You love working in a team. You write readable code, value thorough documentation and clear data lineage, and enjoy collaborating with application engineers to solve complex data delivery problems.

  • Pragmatic Problem Solver – You know when to write a perfectly optimized distributed processing job and when a simple, well-indexed database table or cached view is the smartest move to keep the business moving.

Bonus Points:

  • You’ve worked in a rapidly scaling startup handling complex, multi-tenant B2B SaaS data.

  • You have experience with data quality testing frameworks (like Great Expectations or Soda).

  • You’ve interacted with cloud cost allocation tracking or token-level spend for LLM/AI model integrations.

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.

Frequently Asked Questions

What is the salary for the Data Engineer role at jellyfish?
The listed salary for this Data Engineer position at jellyfish is USD 165K–205K/yr. This is a remote FullTime role.
Is the Data Engineer job at jellyfish remote?
Yes, this Data Engineer position at jellyfish is remote, with team members based in Remote - US. You can work from home or anywhere in the supported regions.
Is the Data Engineer role at jellyfish full-time or part-time?
This is listed as a FullTime position. It is posted as a Data Engineer role in the Engineering department at jellyfish.
Which team or department does the Data Engineer at jellyfish belong to?
This Data Engineer position is part of the Engineering department at jellyfish. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Data Engineer position at jellyfish?
Click the "Apply Now" button on this page. You will be redirected to jellyfish's official application portal hosted on ashby where you can submit your application directly.
When was the Data Engineer job at jellyfish posted?
This Data Engineer position at jellyfish was posted on May 28, 2026. Apply as soon as possible — early applications are often reviewed first.
Data Engineer
jellyfish · 💰 USD 165K–205K/yr
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You'll be redirected to jellyfish's official application page on Ashby ATS.