Data Engineer
· AMSTERDAM, Netherlands ·
- Employment
- Contract
- Category
- Data engineering
Data engineer role at Xccelerated, a Dutch training-and-placement program: after a paid 2-week bootcamp you work 4 days a week at clients like ING, ASML and KLM building data pipelines, warehouses/lakes and productionizing ML models, with Fridays for ongoing training. Core focus: data engineering, containerization and cloud fundamentals.
Data Engineer (NL) - On-site, Hybrid - - Amsterdam , Noord-Holland , Netherlands - Xccelerated
Data Engineer
Ready to break boundaries in the analytical world? Accelerate your data engineering career with our advanced training program. We fully pay this program as well as your salary. Your job? Working as a data engineer at one of our clients like Lely, ING, ASML or KLM on challenging projects. What kind of projects?
✅ Help data-driven organizations move, process and store data by building data warehouses, data lakes and distributed data meshes
✅ Productionizing machine learning models
✅ Apply engineering practices to pick the best tools for the job
✅ Use raw data gathered from data pipelines to build production ready scalable applications driven by data and AI
The role itself -
2 fulltime weeks of hands-on bootcamp training where you'll focus on writing deployable code, containerization, data engineering and cloud fundamentals -
Work 4 days a week as a data engineer at one of our clients like Heineken, Rabobank, ASML, Lely, FedEx, Vattenfall -
Join us every Friday at the Xccelerated office in Amsterdam/ on remote. Here you will get ongoing training and project support from our technical leads -
At the end of your first year, you get the opportunity to join the partner organization directly
As a data engineer you will work together with other medior- and senior team members on challenging projects for our clients. In these projects you take on complex problems such as building data pipelines, productionizing machine learning models and building custom software solutions.
Part of the job is dealing with a variety of data types and formats; different data velocity from batch to near-real time; and scale from one machine to distributed systems. You're not afraid to get your hands dirty with infrastructure, either in the cloud or on-premises. And most importantly you apply engineering practices to pick the best tools for the...
Data Engineer
Ready to break boundaries in the analytical world? Accelerate your data engineering career with our advanced training program. We fully pay this program as well as your salary. Your job? Working as a data engineer at one of our clients like Lely, ING, ASML or KLM on challenging projects. What kind of projects?
✅ Help data-driven organizations move, process and store data by building data warehouses, data lakes and distributed data meshes
✅ Productionizing machine learning models
✅ Apply engineering practices to pick the best tools for the job
✅ Use raw data gathered from data pipelines to build production ready scalable applications driven by data and AI
The role itself -
2 fulltime weeks of hands-on bootcamp training where you'll focus on writing deployable code, containerization, data engineering and cloud fundamentals -
Work 4 days a week as a data engineer at one of our clients like Heineken, Rabobank, ASML, Lely, FedEx, Vattenfall -
Join us every Friday at the Xccelerated office in Amsterdam/ on remote. Here you will get ongoing training and project support from our technical leads -
At the end of your first year, you get the opportunity to join the partner organization directly
As a data engineer you will work together with other medior- and senior team members on challenging projects for our clients. In these projects you take on complex problems such as building data pipelines, productionizing machine learning models and building custom software solutions.
Part of the job is dealing with a variety of data types and formats; different data velocity from batch to near-real time; and scale from one machine to distributed systems. You're not afraid to get your hands dirty with infrastructure, either in the cloud or on-premises. And most importantly you apply engineering practices to pick the best tools for the...