Senior Data Engineer

Your role

We are seeking a highly skilled and experienced Senior Data Engineer to join our growing Data and Analytics team. The ideal candidate will have deep expertise in Databricks and cloud data warehousing, with a proven track record of designing and building scalable data pipelines, optimizing data architectures, and enabling robust analytics capabilities. This role involves working collaboratively with cross-functional teams to ensure the organization leverages data as a strategic asset. Your responsibilities will include:

• Design, build, and maintain scalable data pipelines and ETL processes using Databricks and other modern tools.
• Architect, implement, and manage cloud-based data warehousing solutions on Databricks (Lakehouse Architecture)
• Develop and maintain optimized data lake architectures to support advanced analytics and machine learning use cases.
• Collaborate with stakeholders to gather requirements, design solutions, and ensure high-quality data delivery.
• Optimize data pipelines for performance and cost efficiency.
• Implement and enforce best practices for data governance, access control, security, and compliance in the cloud.
• Monitor and troubleshoot data pipelines to ensure reliability and accuracy.
• Lead and mentor junior engineers, fostering a culture of continuous learning and innovation.
• Excellent communication skills
• Ability to work independently and along with client based out of western Europe.

Who you are

• Bachelors or Master’s degree in Computer Science or a related field.
• 5 years of experience in data engineering roles with a focus on cloud platforms.
• Proficiency in Databricks, including Spark-based ETL, Delta Lake, and SQL.
• Strong experience with one or more cloud platforms (AWS preferred).
• Hands on experience with Delta Lake, Unity Catalog, and Lakehouse architecture concepts
• Strong programming skills in Python and SQL; experience with Pyspark a plus.
• Solid understanding of data modeling concepts and practices (e.g., star schema, dimensional modeling).
• Knowledge of CI/CD practices and version control systems (e.g., Git).
• Familiarity with data governance and security practices, including GDPR and CCPA compliance.

Nice-to-Have Qualifications

• Experience with Airflow or similar workflow orchestration tools.
• Exposure to machine learning workflows and MLOps.
• Certification in Databricks, AWS
• Familiarity with data visualization tools such as Power BI