Databricks Data Engineer

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'. 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 tec...