Senior Data and AI Platform Engineer

Jellyfish

1d•$150,000 - $230,000

About The Position

As a Senior Data and AI Platform Engineer on the Jellyfish Research team, you will support our mission to deliver product innovation, cutting-edge research, and trusted analytics and insights across Jellyfish. You will help build the data and AI platform that powers our internal enterprise-wide analytics, self-service BI, agentic analytics, and AI-enabled workflows. This role is ideal for a senior individual contributor who is excited to combine traditional data engineering with modern data platform ownership. You will still build ingestion, transformation, and data delivery pipelines, but your broader mandate will be to help make Databricks the trusted foundation for analytics and AI across the company. You will play a key role in designing and operating our Databricks Lakehouse, governing our data through Unity Catalog, enabling accurate and scalable BI within Databricks, and building the foundation for agentic analytics using capabilities such as Genie, Databricks Apps, Ontology, and other Databricks-native AI and analytics features. Most importantly, you will be part of a highly talented team working in a fun, challenging, and collaborative environment, building a fast-growing business led by experienced entrepreneurs and backed by top-tier investment partners.

Requirements

Deep experience in data engineering, data platform engineering, analytics engineering, or related roles.
Designed, built, and operated reliable data platforms or large-scale data pipelines in production.
Strong experience with Databricks or similar lakehouse/data platform technologies, and you are excited to help make Databricks a central platform for analytics and AI.
Understand how to build governed, well-modeled data assets that can support BI, analytics, data science, and AI use cases.
Experience with data ingestion, transformation, orchestration, testing, monitoring, and data quality practices.
Advanced SQL skills and experience working with multiple database and warehouse technologies.
Strong programmer, with experience building production-grade systems in Python or similar languages.
Understand the importance of metadata, documentation, lineage, access control, and semantic context in making data trustworthy and usable.
Excited about AI and agentic analytics, but also understand that successful AI depends on strong data foundations, clear definitions, governance, evaluation, and operational discipline.
Comfortable working with technical and non-technical stakeholders, translating ambiguous needs into durable platform capabilities.
Operate as a senior individual contributor: you can lead through architecture, judgment, communication, influence, and execution without needing to be a people manager.
Love learning new things and teaching others what you know.
Strong communication skills and enjoy working as part of a cross-functional team.
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.

Nice To Haves

Experience with Databricks Unity Catalog, Databricks SQL, Lakehouse architecture, Delta Lake, Databricks Workflows, Databricks Apps, Genie, or related Databricks AI/BI capabilities.
Building platforms for self-service analytics, governed BI, semantic layers, metrics layers, or AI-assisted analytics.
Designing data platforms that support LLMs, agents, retrieval-augmented generation, MCP, or other AI-enabled workflows.
Infrastructure-as-code and platform automation tools such as Terraform, Databricks Asset Bundles, CI/CD pipelines, or similar technologies.
dbt and modern analytics engineering practices
Humility, a performance-driven attitude, and a team-player approach.
A sense of humor is a must.

Responsibilities

Design, build, and maintain data platforms and pipelines that support analytics, data science, BI and AI across Jellyfish.
Lead the evolution of Jellyfish’s Databricks Lakehouse platform, helping define the architecture, governance model, development patterns, and operating practices that make the platform reliable, scalable, and easy to use.
Be a leader in enabling enterprise-wide agentic analytics within Databricks with trusted datasets, semantic definitions, well-managed context, and well-governed agentic access.
Help mature core Databricks platform capabilities, including Unity Catalog, governed data access, data lineage, metadata management, compute patterns, environment management, and platform observability.
Build and maintain ingestion pipelines that bring high-value data into the Lakehouse
Partner on data flows that send trusted data to other internal systems
Collaborate with data scientists, analysts, product managers, engineering leaders, customer success leaders, go-to-market leaders, and other stakeholders to understand analytical needs and design durable platform solutions.
Create standards and reusable patterns for data modeling, documentation, observability, testing, governance, and AI-readiness across the data platform.
Develop tools and processes to monitor data platform health, pipeline reliability, cost, performance, usage, and trust.
Provide technical leadership as a senior individual contributor by setting architectural direction, raising engineering standards, mentoring teammates, and helping the team make high-quality technical decisions.
Stay current with emerging Databricks and AI capabilities, evaluate where they can create real value for Jellyfish, and help turn promising ideas into production-ready platform capabilities.