Data Engineer- Python/ SQL

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: 3+ 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., Data Fundamentals: Solid understanding of data warehousing principles, ETL processes, data modeling techniques, and database systems. Advanced SQL skills for data querying, transformation, and analysis. Strong analytical and problem-solving abilities, with a proactive approach to identifying and resolving data-related challenges. Fluent in English and proficiency in Dutch or French is mandatory. Experience with machine learning or AI technologies. Experience with data visualization tools (e.g., Work with innovative and impactful Cloud, Data & AI projects for industry-leading clients At Devoteam, we combine strong values - respect, frankness, ambition, entrepreneurship & collaboration - with a fun and supportive environment that empowers you to innovate, grow, and succeed in the fast-paced world of Cloud, Data & AI.

Devoteam is a leading consulting firm focused on digital transformation. We help our clients leverage technology to achieve their business goals. Our longstanding partnerships with leaders like AWS, Google Cloud, Microsoft, and ServiceNow amplify our capabilities, allowing us to deliver top-tier expertise and award-winning services. We complement these partnerships with in-depth Cyber, Data & AI, Software development and multi cloud expertise. For 30 years, we have always been guiding our customers on the next tech wave . Devoteam has guided organizations through the Internet and cloud. With 11,000 tech natives working in 25+ countries, we bring you highly skilled IT experts across Europe At Devoteam, tech is in our DNA , and it's the people we empower with tech. Now, with responsible AI, we're ready to unlock a future where technology drives positive change. We are seeking a talented and passionate Databricks Data Engineer to join our expanding Data & AI team Databricks Partner (50 FTE) . 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. 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.). 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