Research Data Engineer

Embodied AI; Ecublens; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Embodied AI in Lausanne, Switzerland is seeking a Research Data Engineer to build the analysis library used by engineering teams to turn test data into decisions and to connect data flows from layout through measurement.

You will own the infrastructure, design a Python library for characterization data orchestration, and develop scalable ETL/ELT pipelines with Prefect, Airflow or Dagster, while ensuring traceability and cross‑team collaboration.

Qualifikationen

• MSc in Computer Science, Engineering, or a scientific discipline.
• 5+ years of data experience in R&D or instrument-heavy environments.
• Strong Python experience and library/API design.
• Proficiency with SQL, Git, and UNIX/bash.
• Experience building ETL/ELT pipelines with Prefect, Airflow, Dagster.
• Familiarity with scientific data formats (HDF5, Zarr, Parquet) and storage concepts.

Aufgaben

• Architect a Python library centered on pipeline orchestration for characterization data.
• Ensure abstraction between analysis logic and underlying file formats or storage schemas.
• Develop scalable solutions for local, remote, and distributed execution environments.
• Integrate logging and transformation lineage for dataframes with database export capabilities.
• Cater to both exploratory R&D and production-level quality assurance workflows.
• Provide documentation and support to facilitate technical adoption across internal teams.

Kenntnisse

Python

SQL

Git

UNIX/Bash

Data orchestration

English communication

Ausbildung

MSc in Computer Science, Engineering, or a scientific discipline

Tools

Prefect

Airflow

Dagster

HDF5

Zarr

Parquet

Jobbeschreibung

About us

We're a multicultural team of experts pushing the boundaries of what's possible in integrated optics. Our mission is to make photonic integration accessible and industrially scalable. We deliver best-in-class PIC platforms, design enablement, and integrated solutions that empower our customers to innovate faster and bring light-based technologies from concept to production.

About the role

As a Research Data Engineer, you will build the analysis library our engineering teams use to turn test data into decisions, and connect the data flows that feed it. Both build on existing data infrastructure. In this high-impact position, you will own the infrastructure and conventions that let data move reliably between teams and stay traceable from layout through to measurement, working directly with the people who use what you build.

Role and Responsibilities

Analysis library:

• Architect a Python library centered on pipeline orchestration for characterization data.
• Ensure abstraction between analysis logic and underlying file formats or storage schemas.
• Develop scalable solutions for local, remote, and distributed execution environments.
• Integrate logging and transformation lineage for dataframes with database export capabilities.
• Cater to both exploratory R&D and production-level quality assurance workflows.
• Provide documentation and support to facilitate technical adoption across internal teams.

Data flow and lineage:

• Build multi-site infrastructure for test data and metadata storage.
• Develop ingestion mechanisms for relational database metadata updates.
• Enable cross-team automation via metadata handshakes and metrology plan scripting.
• Standardize retrieval and storage conventions to ensure end-to-end data traceability.

What you bring

• MSc in Computer Science, Engineering, or a scientific discipline (or equivalent practical experience).
• 5+ years of experience working with data in an R&D, research center, or instrument-heavy environment.
• Strong Python expertise with experience designing libraries and APIs.
• Proficiency with SQL, Git, and UNIX/bash.
• Experience building and running ETL/ELT pipelines with modern orchestrators (Prefect, Airflow, Dagster, or similar) in production.
• Familiarity with scientific data formats (HDF5, Zarr, Parquet) and structured data storage concepts (object storage, relational catalogs).
• Strong written and spoken English skills; ability to coordinate and unify workflows across independent teams.
• Openness to adopting new frameworks and state-of-the-art data tools.

Nice to have

• Domain expertise in integrated photonics or wafer-level fabrication processes.
• Practical experience with distributed computing frameworks (Ray, Dask, Spark) and high-volume data handling.
• Knowledge of data lineage systems and metadata cataloging solutions.

What we offer

A dynamic role at the heart of the deep-tech revolution where your technical expertise directly impacts product adoption. You will join an international team of specialists, gain deep exposure to market-leading photonic applications, and shape how photonic integration is deployed worldwide.

Practicalities

• Location: Lausanne, Switzerland (Onsite).
• Work percentage: 100%.
• Languages: English is our working language, other languages are a plus.
• Home office: Up to two days per week.
• Start date: As soon as possible.

We are an equal-opportunity employer and welcome applications from all backgrounds.