Vacant job

As a growing deep-tech startup in the semiconductor industry, we are seeking a Data Platform Engineer to develop and maintain an in-house data ingestion and analytics platform.

Key Responsibilities

Custom SOP-driven Data Ingestion (Upstream):

• Support internal and external data producers with UI tools and co-development of purposeful data contracts, enabling the ingestion of unstructured data sources such as scientific instrument data, physical measurements, manual logistics, and their canonical storage.
• Develop and maintain data validation procedures to ensure robustness and quality for downstream data pipelines.

Custom S3 Data Lake Management (Infra/Platform):

• Own the architecture, IAM management, ETL design, and development of this (relatively small-scale) data lake infrastructure to ensure availability, integrity, and security. Manage the serving of curated datasets to data consumers and insight subscribers.

Analytics / ML (Downstream):

• Support the organization with traceability and performance tracking of our core business semiconductor process flow in both R&D and production phases. Help the company answer scientific and product-oriented questions with data. Develop own models and derive actionable insights via automated reports, dashboards, and statistics.

Some expected tasks:

- Organization-wide support with onboarding of new SOPs requiring data contracts.

- Develop workflows and test strategies to ensure end-to-end data quality.

- Support data producers with troubleshooting and upload guidance.

- Develop custom UI and data tools.

- Monitor and debug ingestion failures, ensuring high data quality and consistency.

- Perform exploratory data analysis, statistical reporting, and machine learning modeling on curated datasets.

- Document SOP onboarding processes, data validation rules, and platform workflows.

- Collaborate with scientific and engineering teams to plan future platform improvements.

Desired Skills & Qualifications

- Strong proficiency in Python and data validation workflows.

- Proficient in S3-like object storage: Experience managing and utilizing object storage solutions for data management.

- Cloud Computing: Knowledge of setting up and configuring cloud compute instances, ensuring efficient resource allocation and deployment.

- Knowledge of schema validation (e.g., JSON Schema) and ETL/data ingestion patterns.

- Ability to design, validate, and evolve ETL and data pipelines.

- Experience with data cleaning, wrangling, and quality control processes.

- Comfortable communicating and presenting in English.

Preferred Qualifications

- Background in engineering, physics, or a similar technical domain.

- Experience with machine learning tools (scikit-learn).

- Familiarity with laboratory workflows or process data environments.

- Experience with visualization libraries (e.g., Matplotlib, Seaborn, Plotly).

- Understanding of modern tooling (CI/CD, version control, testing frameworks).

Personal Attributes

- Structured and detail-oriented.

- Strong communicator who enjoys supporting colleagues.

- Thrives in a cross-functional, highly dynamic environment.