Data Engineer
Share
Job Location:
Zürich - Switzerland
Monthly Salary:
Not Disclosed
Posted on:
10 hours ago
Vacancies:
1 Vacancy
Job Summary
About Us
Manukai stands for Manufacturing and Kaizen a Japanese methodology of continuous improvement that translates to change for ancient Greek Kairos means the opportune moment.
We are a spin-off from ETH Zürich aiming to bridge the gap between metal part design and machining. Our AI-powered technology empowers manufacturers to prioritize their clients needs and deliver high-quality products to the market. Our primary focus is making an immediate impact with client satisfaction as our utmost priority.
The Role
You will own data reliability scalability and efficiency across Manukais systems. You will accelerate data-driven decision making and lay the groundwork for machine learning by delivering high-quality data and quantitative reports. You will build automation to scrape generate visualize and label data; design and manage data warehouses; and collaborate closely with machine learning engineers and the founding team to ensure data needs are met. We value proactive contributors who bring ideas that shape our product and company.
About You
You are a team player who enjoys technical challenges. You appreciate short decision paths and can drive your ideas autonomously from concept to production. You contribute thoughtfully to architecture design and code reviews. You remove hurdles thrive in a dynamic environment with evolving requirements and are eligible to work in Switzerland.
Tasks
- Build tools to scrape visualize analyze and label data
- Label scraped and customer-provided datasets
- Work with multiple CAM systems for data extraction and analysis
- Support the design and development of machine learning algorithms to generate synthetic data
- Validate machine learning algorithms using generated datasets
- Ensure data needs are met across all teams
- Automate and optimize processes and workflows
- Maintain high software quality and sustainable development; review teammates code for best practices (for example testability efficiency and style)
Data You Will Work With
- CAM artifacts such as toolpaths geometry machining parameters and simulation outputs
- B-reps (for example STEP files) and derived quantities
- Outputs of proprietary ML algorithms
Requirements
- Degree (BSc MSc or PhD) in a quantitative field or 3 years of professional software development experience in lieu of a degree
- Strong numerical and analytical skills
- Solid understanding of statistics and data interpretation
- Good knowledge of Python
- Good knowledge of common data engineering tools (for example Airflow dbt Spark Pandas/Polars)
- Knowledge of the Linux operating system
- Good knowledge of machine learning practices
- Experience with databases and data modeling including SQL (PostgreSQL SQLite) and NoSQL (MongoDB)
- Experience with CAD
- Good understanding of version control testing continuous integration build deployment and monitoring
- Sound software design and an agile development mindset
Benefits
- Personal growth potential: You will be a key team member and part of the success story.
- Equity participation: Youll have the opportunity to share in the companys success through our stock option plan.
- Personal development: Dedicated time to pursue your personal interests and goals.
- Time off and flexibility: Generous vacation and flexible work hours.
- Pension plan: Generous and competitive.
- Location: Zürich or remote.
At Manukai we work on real problems with real impact. We combine advanced AI algorithms human-centered design and deep respect for craftsmanship in manufacturing. If youre looking for meaningful work a sharp team and a culture that cares wed love to meet you.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
Manukai stands for Manufacturing and Kaizen a Japanese methodology of continuous improvement that translates to change for better. In ancient Greek Kairos means the opportune moment.We are a spin-off from ETH Zürich aiming to bridge the gap between metal part design and machining. Our ... View more
