Databricks Machine Learning Engineer - Berlin
SECUSTAFF GmbH
3 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Shift work Languages
English, German Experience level
SeniorJob location
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Unit Testing
Azure
Big Data
Continuous Integration
Information Engineering
Relational Databases
Software Debugging
Linux
Python
Machine Learning
Microsoft SQL Server
MySQL
SAP HANA
Software Engineering
SQL Databases
Google Cloud Platform
Spark
Operational Systems
Software Coding
Databricks
Programming Languages
Job description
- Implementation and production readiness of ML-based services on our AI and big data platform Databricks using Python, SQL and Linux.
- Advising and supporting cross-functional teams in setting up efficient and scalable big data and data science projects, as well as taking on production responsibility to ensure continuous business value.
- Improving standard processes and best practices for services and projects on our platform and helping to reduce costs for these.
- Write clean, maintainable, and efficient code following best practices and coding standards, and perform unit testing and debugging to ensure high quality software delivery.
- Collaborate with neighbouring teams on topics such as governance, infrastructure (on AWS, GCP, and Azure), data provisioning and planning, CI/CD, and data engineering.
- Staying up to date with relevant industry trends and technologies and applying them to improve our software and service offerings.
Requirements
- Have at least 2+ years of experience in machine learning engineering on Databricks, including experience with Unity Catalogue, asset bundles, workspace creation, ML Flow, Lakebase and Python.
- Have at least 5+ years of experience working in software engineering with at least one additional high-level programming language.
- Have a solid understanding of SQL and experience working with relational databases (HANA, MS SQL, MySQL).
- Have advanced knowledge of Linux and operating systems and of creating, configuring, using and debugging Spark clusters.
- Offer strong problem-solving skills and the ability to work independently as well as part of a team.
- Have good communication and presentation skills in English and at least basic skills in German.
Benefits & conditions
- Flexible working hours and mobile working (usually 3 days per week)
- 30 days of annual vacation (full-time; pro rata for part-time)
- Performance-based bonus and company car option
- Company smartphone and modern work equipment
- Workation (up to 30 days per year in selected countries)
- Sabbatical (after 3 years of employment)
- Comprehensive onboarding day and personalized training program
- Health and fitness programs
- Fresh fruit days, health days, company sports groups, and running clubs
- Career and development programs
- Flat hierarchies and a culture of appreciation
- Employee events and corporate benefits program
- Free hot and cold beverages at most locations
- Employee referral program ("Employees recruit employees")
- Loyalty bonuses, anniversary gifts, birth and wedding allowances
- Relocation cost reimbursement (under certain conditions)
- JobRad (company bike) and JobTicket (public transport subsidy)
