Senior Data Engineer II

Jellyvision is redefining how organizations experience benefits by bringing everything together in one modern, intelligent home. As a Senior Data Engineer, you'll be a hands-on engineer on a high-ownership data team responsible for building and operating data pipelines, improving existing data systems, and maintaining data infrastructure.

Responsibilities:

• Design and build pipelines that support data movement across systems - ingestion, transformation, compliance, and cross-domain data flows
• Own pipeline operations end to end: monitoring, incident resolution, and data quality across both new and inherited workloads
• Make sound pipeline design decisions independently while working within the architecture the team has established
• Develop working knowledge of how existing infrastructure fits together by mapping data flows, dependencies and performance characteristics
• Improve documentation, observability, data quality, and operational standards across the systems you work in
• Identify technical debt and reliability risks and bring recommendations grounded in meaningful impact
• Provision and manage the infrastructure your data workloads require, using established IaC practices and team standards
• Contribute to shared infrastructure as the platform evolves, building on new foundations as they become available
• Maintain and improve the reliability, performance, and cost-efficiency of the infrastructure you own
• Build enough working knowledge of the team's full system footprint to step in when priorities shift or teammates are unavailable
• Contribute to platform work as needed — you won't own the new build, but you should be ready to support it when the team needs flexibility

Requirements:

• 6–8+ years of data engineering experience with hands-on ownership of production systems
• Strong pipeline design and orchestration skills in a production environment
• Advanced SQL: complex transformations, performance tuning, and debugging against a cloud data lake or warehouse
• Strong Python: production-grade code, scripting, testing, and debugging
• Working knowledge of infrastructure-as-code for provisioning and managing cloud data resources
• Familiarity with AWS data infrastructure: S3, IAM, and relevant managed services
• Experience inheriting and improving systems you didn't build - developing working knowledge, identifying risks, and making them better
• Clear written communication: you can document a system, a process, or a recommendation so others can act on it independently
• Comfortable working across team boundaries with engineering and product on data needs
• Experience using AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) to accelerate engineering workflows
• Data science or analytics background — comfortable with model inputs and outputs, statistical concepts, and supporting analytical or decision-support workflows
• Experience with dbt or comparable transformation frameworks: reading models, understanding grain and dependencies, writing tests
• Experience with managed ELT tools (Fivetran, Stitch, or similar)
• Experience in a regulated industry (healthcare, insurance, financial services) with familiarity around compliance-driven data requirements
• SaaS platform experience, particularly with multi-tenant data architectures