About the 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.
