Senior Data Platform Engineer

Tessera Labs

2d•$200,000 - $300,000•Remote

About The Position

Tessera Labs is seeking a Data Platform Engineer to build software that connects enterprise systems and makes their data usable across applications, analytics, and AI. The role sits at the intersection of backend engineering and data systems, developing reusable capabilities for connecting to, querying, moving, and processing data. The position is open to remote candidates, with a preference for candidates based in the Bay Area. The engineer will build and operate core data platform capabilities, including services and APIs for data access, query execution, ingestion, and synchronization. They will develop reusable connector frameworks, improve query and data-movement performance, and ensure workloads recover reliably from failures while preserving data correctness. The role partners with product and engineering teams to define interfaces, make architectural decisions, and take capabilities from design through production. Tessera Labs builds multi-agent AI systems that automate complex business workflows across enterprise platforms. The company describes its working ethos as enterprise serious and AI forward, with an emphasis on speed, ownership, and applied AI.

Requirements

At least 4 years of experience as a Data Platform Engineer.
Strong Python and SQL skills, with experience building maintainable, tested production software.
Experience developing backend services, data infrastructure, or data platform components, beyond configuring pipelines.
Solid understanding of relational databases, query optimization, data formats, and the tradeoffs between querying data in place and materializing it elsewhere.
Experience with concurrent or distributed workloads, including failure handling, resource management, and performance debugging.
Ability to investigate unfamiliar systems and turn complex requirements into clear, practical designs.

Nice To Haves

Experience with analytical query engines, lakehouse technologies, workflow orchestration, enterprise-system integrations, or containerized infrastructure.
Experience building connector libraries, developer-facing APIs, or shared platforms used by other engineering teams.
Familiarity with cloud infrastructure such as AWS, Azure, or GCP, including networking, storage, identity and access management (IAM), and infrastructure as code.

Responsibilities

Develop services and APIs for data access, query execution, ingestion, and synchronization.
Build reusable connector frameworks and abstractions for different systems and access patterns.
Identify bottlenecks in querying and data movement and improve performance through partitioning, parallelism, and effective memory and storage management.
Build orchestration, retries, checkpointing, and observability to support predictable workload recovery and data correctness.
Work with product and engineering teams to define interfaces and make architectural tradeoffs.
Take platform capabilities from design to production and operate the systems built.