Data Engineer (Databricks)

Addepto is a leading AI consulting and data engineering company that builds scalable, ROI-focused AI solutions for large enterprises and startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. The company focuses exclusively on Artificial Intelligence and Big Data, helping organizations unlock the potential of their data for measurable business impact and growth. Addepto is part of KMS Technology, a US-based global technology group, combining AI specialization with enterprise-scale delivery capabilities.

• At least 3 years of commercial experience implementing, developing, or maintaining Big Data systems.
• Strong programming skills in Python including clean code and OOP design.
• Strong SQL skills including performance tuning, query optimization, and experience with data warehousing solutions.
• Experience designing and implementing data governance and data management processes.
• Deep expertise in Big Data technologies including Databricks, Spark, Apache Airflow, and other modern data orchestration and transformation tools.
• Experience implementing and deploying solutions in cloud environments, preferably Azure.
• Knowledge of building and deploying Power BI reports and dashboards for data visualization.
• Excellent understanding of dimensional data and data modeling techniques.
• Consulting experience with ability to guide clients through architectural decisions, technology selection, and best practices.
• Ability to work independently and take ownership of project deliverables.
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or related field.

Nice to have:

• Experience with CI/CD, Kubernetes, Kafka, Power BI, Airflow, Dagster, dbt.

• Design and optimize scalable data processing pipelines for streaming and batch workloads using Big Data technologies such as Databricks, Apache Airflow, and Dagster.
• Architect and implement end-to-end data platforms ensuring high availability, performance, and reliability.
• Lead development of CI/CD and MLOps processes to automate deployments, monitoring, and model lifecycle management.
• Develop and maintain applications for aggregating, processing, and analyzing data from diverse sources ensuring efficiency and scalability.
• Collaborate with Data Science teams on Machine Learning projects including text/image analysis, feature engineering, and predictive model deployment.
• Design and manage complex data transformations using Databricks, DBT, and Apache Airflow ensuring data integrity and consistency.
• Translate business requirements into scalable and efficient technical solutions while ensuring optimal performance and data quality.
• Ensure data security, compliance, and governance best practices are followed across all data pipelines.