Amsterdam, NH, Netherlands
Live, first seen by us 74 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design, build and deploy scalable data pipelines on Databricks
Transform and cleanse data with Spark and load it into lakes and warehouses
Optimize pipeline performance for efficiency and cost
Implement data quality checks and validation throughout pipelines
Integrate Databricks with Azure, AWS or GCP storage and compute
Design, develop, and deploy robust and scalable data pipelines using Databricks
transformation and cleansing using Spark, and loading into target systems (data lakes, data warehouses, etc.)
Optimize pipeline performance for efficiency and cost-effectiveness
Implement rigorous data quality checks and validation procedures throughout the data pipeline
Seamlessly integrate Databricks with cloud services (Azure, AWS, or GCP)
Functie-eisen - Hold a University Degree in Computer Science, (Business) Engineering, or a specialized master's in Machine Learning or AI. - Proven Experience: 2+ years of experience as a Data Engineer with demonstrated expertise in Databricks.
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Day 74
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Devoteam’s usual: its jobs come down by about day 22.
From 13,630 similar postings that came down, and 152 of Devoteam’s. Coming down is not always a hire.
44 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Cloud Proficiency: Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), with a good understanding of cloud data services and infrastructure. - Programming Skills: Strong programming skills in Python or Scala, with experience in data manipulation libraries (e.g., PySpark, Spark SQL). - Data Fundamentals: Solid understanding of data warehousing principles, ETL processes, data modeling techniques, and database systems.
- Data Pipeline Engineering: Design, develop, and deploy robust and scalable data pipelines using Databricks, incorporating data extraction from diverse sources (databases, APIs, streaming platforms), transformation and cleansing using Spark, and loading into target systems (data lakes, data warehouses, etc.). Optimize pipeline performance for efficiency and cost-effectiveness. - Databricks Ecosystem Expertise: Utilize the full capabilities of the Databricks platform, including Databricks SQL, Delta Lake, Databricks Runtime, and Databricks Workflows, to orchestrate complex data workflows and ensure data quality and pipeline reliability. - Cloud Integration: Seamlessly integrate Databricks with cloud services (Azure, AWS, or GCP) for storage, compute, and security, leveraging services like Azure Data Lake Storage, AWS S3, Google Cloud Storage, and more.
- Data Fundamentals: Solid understanding of data warehousing principles, ETL processes, data modeling techniques, and database systems. - SQL Expertise: Advanced SQL skills for data querying, transformation, and analysis. - Communication Skills: Excellent communication and interpersonal skills, with the ability to effectively collaborate with technical and non-technical stakeholders.
- Databricks Ecosystem Expertise: Utilize the full capabilities of the Databricks platform, including Databricks SQL, Delta Lake, Databricks Runtime, and Databricks Workflows, to orchestrate complex data workflows and ensure data quality and pipeline reliability. - Cloud Integration: Seamlessly integrate Databricks with cloud services (Azure, AWS, or GCP) for storage, compute, and security, leveraging services like Azure Data Lake Storage, AWS S3, Google Cloud Storage, and more. - Data Architecture and Modeling: Contribute to the design and implementation of robust data models and architectures for data lakes and data warehouses, ensuring data consistency, integrity, and accessibility for various use cases.
- Proven Experience: 2+ years of experience as a Data Engineer with demonstrated expertise in Databricks. - Cloud Proficiency: Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), with a good understanding of cloud data services and infrastructure. - Programming Skills: Strong programming skills in Python or Scala, with experience in data manipulation libraries (e.g., PySpark, Spark SQL).
Who are we? We are Devoteam, an AI-driven tech consultancy with more than 11,000 tech experts spread across 25 countries in Europe and the Middle East. At Devoteam, we strongly believe in the power of technology, with AI at the heart of our approach. We partner with leading providers such as Google, Microsoft, AWS, and ServiceNow. In the Netherlands, we have around 300 experts and specialize in Cloud, Cyber, Data, and AI. With us, you become part of a group of Tech Enthusiasts in a culture where making mistakes is allowed and where everyone—from bright young talents to experienced rockstars—is encouraged to continuously innovate and grow. We are a community that is proud of who you are and helps you get the best out of yourself. We are allergic to unnecessary hierarchies and excessive processes. At Devoteam, the only constant is 'change'.
Vacatureomschrijving We are seeking a talented and passionate Databricks Data Engineer to join our expanding Microsoft Databricks team. In this role, you will be a crucial player in designing, building, and maintaining cutting-edge data solutions on the Databricks platform. You will have the opportunity to work with a variety of clients across different industries, collaborating with both internal teams and client stakeholders to deliver high-quality data pipelines and enable data-driven decision-making. Responsibilities:
Responsibilities: - Data Pipeline Engineering: Design, develop, and deploy robust and scalable data pipelines using Databricks, incorporating data extraction from diverse sources (databases, APIs, streaming platforms), transformation and cleansing using Spark, and loading into target systems (data lakes, data warehouses, etc.). Optimize pipeline performance for efficiency and cost-effectiveness. - Databricks Ecosystem Expertise: Utilize the full capabilities of the Databricks platform, including Databricks SQL, Delta Lake, Databricks Runtime, and Databricks Workflows, to orchestrate complex data workflows and ensure data quality and pipeline reliability.
- Data Quality Assurance: Implement rigorous data quality checks and validation procedures throughout the data pipeline to maintain high accuracy and reliability. Adhere to data governance policies and best practices. - Collaboration and Communication: Work closely with data scientists, analysts, business intelligence specialists, and business stakeholders to understand their data requirements and provide technical expertise on Databricks and data engineering best practices. - Continuous Learning: Stay up to date with the latest Databricks features, cloud technologies, and data engineering trends to continuously improve our solutions and deliver innovative results for our clients.
- Collaboration and Communication: Work closely with data scientists, analysts, business intelligence specialists, and business stakeholders to understand their data requirements and provide technical expertise on Databricks and data engineering best practices. - Continuous Learning: Stay up to date with the latest Databricks features, cloud technologies, and data engineering trends to continuously improve our solutions and deliver innovative results for our clients. Functie-eisen
- Hold a University Degree in Computer Science, (Business) Engineering, or a specialized master's in Machine Learning or AI. - Proven Experience: 2+ years of experience as a Data Engineer with demonstrated expertise in Databricks. - Cloud Proficiency: Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), with a good understanding of cloud data services and infrastructure.
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Yes. We’ve followed one other Databricks Data Engineer job there since May 2026. It is still up.
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
We are seeking a talented and passionate Databricks Data Engineer to join our expanding Microsoft Databricks team. In this role, you will be a crucial player in designing, building, and maintaining cutting-edge data solutions on the Databricks platform. You will have the opportunity to work with a variety of clients across different industries, collaborating with both internal teams and client stakeholders to deliver high-quality data pipelines and enable data-driven decision-making.
Responsibilities:
Data Pipeline Engineering: Design, develop, and deploy robust and scalable data pipelines using Databricks, incorporating data extraction from diverse sources (databases, APIs, streaming platforms), transformation and cleansing using Spark, and loading into target systems (data lakes, data warehouses, etc.). Optimize pipeline performance for efficiency and cost-effectiveness.
Databricks Ecosystem Expertise: Utilize the full capabilities of the Databricks platform, including Databricks SQL, Delta Lake, Databricks Runtime, and Databricks Workflows, to orchestrate complex data workflows and ensure data quality and pipeline reliability.
Cloud Integration: Seamlessly integrate Databricks with cloud services (Azure, AWS, or GCP) for storage, compute, and security, leveraging services like Azure Data Lake Storage, AWS S3, Google Cloud Storage, and more.
Data Architecture and Modeling: Contribute to the design and implementation of robust data models and architectures for data lakes and data warehouses, ensuring data consistency, integrity, and accessibility for various use cases.
Data Quality Assurance: Implement rigorous data quality checks and validation procedures throughout the data pipeline to maintain high accuracy and reliability. Adhere to data governance policies and best practices.
Collaboration and Communication: Work closely with data scientists, analysts, business intelligence specialists, and business stakeholders to understand their data requirements and provide technical expertise on Databricks and data engineering best practices.
Continuous Learning: Stay up to date with the latest Databricks features, cloud technologies, and data engineering trends to continuously improve our solutions and deliver innovative results for our clients.
Hold a University Degree in Computer Science, (Business) Engineering, or a specialized master's in Machine Learning or AI.
Proven Experience: 2+ years of experience as a Data Engineer with demonstrated expertise in Databricks.
Cloud Proficiency: Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), with a good understanding of cloud data services and infrastructure.
Programming Skills: Strong programming skills in Python or Scala, with experience in data manipulation libraries (e.g., PySpark, Spark SQL).
Data Fundamentals: Solid understanding of data warehousing principles, ETL processes, data modeling techniques, and database systems.
SQL Expertise: Advanced SQL skills for data querying, transformation, and analysis.
Communication Skills: Excellent communication and interpersonal skills, with the ability to effectively collaborate with technical and non-technical stakeholders.
Problem-Solving: Strong analytical and problem-solving abilities, with a proactive approach to identifying and resolving data-related challenges.
Proficiency in Dutch is a big plus.
At Devoteam, we invest in our people. Our benefits package includes:
Excellent primary and secondary employment benefits (excellent salary, bonus, lease car, laptop, phone, etc.).
A personalized career development plan with specific training and certifications tailored to your field.
Every opportunity to grow as a thought leader through knowledge sharing, blogs, and keynote sessions.
The unique option to work from within Europe for 4 weeks per year.
A vibrant internal community with knowledge sessions, ranging from bi-weekly Tech Thursdays to KISSes (Knowledge & Information Sharing Sessions).
We look forward to welcoming you into our open and accessible culture! Are you ready for your next challenge? Apply today!
Questions? Please contact Casper Posch at nl.recruitment@devoteam.nl.
Who are we?
We are Devoteam, an AI-driven tech consultancy with more than 11,000 tech experts spread across 25 countries in Europe and the Middle East. At Devoteam, we strongly believe in the power of technology, with AI at the heart of our approach. We partner with leading providers such as Google, Microsoft, AWS, and ServiceNow. In the Netherlands, we have around 300 experts and specialize in Cloud, Cyber, Data, and AI.
With us, you become part of a group of Tech Enthusiasts in a culture where making mistakes is allowed and where everyone—from bright young talents to experienced rockstars—is encouraged to continuously innovate and grow. We are a community that is proud of who you are and helps you get the best out of yourself. We are allergic to unnecessary hierarchies and excessive processes. At Devoteam, the only constant is 'change'.
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Amsterdam, NH, Netherlands
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