Jellyfish
Engineering
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Jellyfish. Skills: Python, SQL, data pipelines, data modeling. Maintain data pipelines. Write Python and SQL”
What You'll Achieve.
build, automate, and execute the next generation of our Jellyfish data platform; implementing core data models; building production-grade CI/CD for data pipelines; transforming raw engineering signals into highly optimized analytical layers; write code that directly impacts how the world’s best engineering leaders measure their output; ensure the issue never happens again
Industry & Context.
Pragmatic Problem Solver; solve complex data delivery problems
On-Call & Observability Triage, Occasional travel may be required, Applicants must be authorized to work for any employer in the US, unable to sponsor or take over sponsorship of an employment visa
What They're Looking For.
Must Have
Python, SQL, data transformation frameworks, workflow orchestration engines, enterprise data platforms, data deployments, automated tests, data quality, application backend tiers, backend-for-frontend (BFF) layers, Redis caching structures, data platform's incident response rotation, observability, alerts, programmatic fixes
Nice to Have
rapidly scaling startup, complex, multi-tenant B2B SaaS data, data quality testing frameworks, Great Expectations, Soda, data-observability patterns, cloud cost allocation, token-level spend for LLM/AI model integrations
What You'll Do.
Maintain data pipelines
Migrate workflow orchestration engines
Optimize workflow orchestration engines
Maintain workflow orchestration engines
Eliminate pipeline bottlenecks
Ensure distributed tasks scale
Build data deployments
Provision data resources
Write automated tests
Validate schemas and data quality
Collaborate with product developers
Design application backend tiers
Optimize application backend tiers
Design Redis caching structures
Optimize Redis caching structures
Participate in incident response rotation
Build deep observability
Write programmatic fixes
How You'll Work.
Team & Collaboration
Working closely with Lead Data Architect; Collaborate with product developers; Collaborating with application engineers
Communication Scope
clear data lineage
Full Job Description
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 Senior Data Engineer to help us build, automate, and execute the next generation of our Jellyfish data platform. Working closely with our Lead Data Architect, you’ll be responsible for implementing core data models, building production-grade CI/CD for data pipelines, and transforming raw engineering signals into highly optimized analytical layers. If you view broken pipelines and manual data patches as a technical debt to be solved 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: - Pipeline Execution & Modeling – You’ll maintain our end-to-end data pipelines, writing clean, modular Python and SQL. You will help translate the architectural blueprint into reality, structuring data across our Medallion layers (Bronze > Silver > Gold) for maximum performance and reliability. - Orchestration Modernization – You’ll take the lead on migrating, optimizing, and maintaining our workflow orchestration engines. You’ll eliminate pipeline bottlenecks, leverage modern fast-paths (like Pydantic v2 and async database clients), and ensure distributed tasks scale seamlessly without hitting API limits. - Data CI/CD & Infrastructure Automation – You’ll build the "paved road" for data deployments. You’ll use Terraform to provision data resources and write automated tests to validate schemas and data quality before code ever hits our isolated staging or production catalogs. - API & Caching Integration – You’ll collaborate with product developers to expose data safely. You’ll help design and optimize 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 & Observability Triage – You’ll par
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