About Xanadu:
Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.
At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. What we are doing is extremely hard, the classic moon shot. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems and literally change the world. And that is something to be excited about!
Your role and responsibilities:
As a Data Platform Engineer, you will take Xanadu’s existing data pipelines and transform them into a cohesive data platform. Working alongside hardware researchers, data scientists, and finance analysts, you'll define how data flows across the organization and build the infrastructure that enables data-driven decisions at every level. This is a hands-on technical role first — you will be the first dedicated data engineer, with the opportunity to build a data team around you.
This is a high-complexity, moderate-volume problem. Terabytes, not petabytes. Different heterogeneous measurement types, not billions of uniform events.
Your responsibilities will be:
- Design, build and maintain a robust cloud data infrastructure (ingestion, transformation, serving) that will serve multiple engineering team across the organization
- Own the data architecture: layering, schema and contract design, materialization strategy, query performance.
- Understand and consolidate existing data workflows and pipelines spanning R&D, manufacturing, and business analytics
- Define data models in collaboration with researchers and analysts to ensure scientific and business data is stored correctly and queryable
- Establish data governance foundations: lineage, cataloging, access control, and quality monitoring
- Drive best practices across code quality, testing, data reliability, and observability
- Balance new development, platform improvements, and technical debt reduction
- Mentor and provide technical guidance to engineers across the organization as the practice grows
Basic qualifications and experience:
- 7+ years in data engineering, with 2+ years in a lead or architect capacity
- Deep experience building and scaling data platforms in the cloud from the ground up
- Strong software engineering: Python packaging, testing, CI
- Production experience designing and operating data lake or lakehouse architectures (Delta Lake, Iceberg, or Hudi)
- Hands-on experience with modern data stack tooling (dbt or similar) and orchestration (Airflow, Dagster, Prefect)
- Strong SQL skills
- Knowledge of infrastructure-as-code and CI/CD for data pipelines
- Proven ability to drive technical standards and engineering improvements across teams
- Experience working with cross-functional teams — especially R&D or science teams producing unstructured or semi-structured data
Preferred qualifications and experience
- Experience in a deep-tech, hardware, or semiconductor environment where data originates from physical measurement systems
- Familiarity with time-series or scientific data formats (HDF5, Parquet for measurement traces, etc.)
- Prior experience as the "first data engineer" — building a practice from scratch, not inheriting one
- Familiarity with LIMS systems or laboratory data workflows
This is for a new position. Your base salary will be determined based on your location, experience, and internal benchmarks. You will also be eligible for equity and benefits.
