Data Platform Engineer
- Toronto, ON
- Sur place
- Publié 18 sept. 2026
- 1 poste
Ouvre un site externe
- Type d’emploi
- Temps plein
- Niveau d’expérience
- Expérimenté · 5+ ans
- Postuler avant le
- 15 oct. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Niveau d’expérience
- Mid-Senior level
Résumé du poste
Design and build a robust cloud data infrastructure to transform existing pipelines into a cohesive data platform. Define data architecture, models, and governance to enable data-driven decisions across R&D, manufacturing, and business analytics.
Détails du poste
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. Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values here. We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at recruiting@xanadu.ai. Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Ce que vous ferez
Design and build a robust cloud data infrastructure to transform existing pipelines into a cohesive data platform. Define data architecture, models, and governance to enable data-driven decisions across R&D, manufacturing, and business analytics.
Exigences
Requires over 7 years of data engineering experience with a strong background in Python, SQL, and cloud lakehouse architectures. Candidates should have proven experience leading data platform builds and working with cross-functional science or R&D teams.
Avantages
• Equity • Benefits
Compétences indiquées
- SQL · Souhaitée
- CI/CD · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Data Engineering
- Cloud Data Infrastructure
- Python
- SQL
- Data Lakehouse
- dbt
- Airflow
- Infrastructure-as-Code
- CI/CD
- Data Modeling
- Data Governance
- Data Architecture
- Dagster
- Prefect
- Delta Lake
- Iceberg
Domaines d’emploi
- Data & Analytics
- Technology
- Engineering
- Software
- Science & Research
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