Senior 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. They focus on Artificial Intelligence and Big Data, helping organizations unlock the potential of their data for measurable business impact and growth. The company is part of KMS Technology, offering global technology delivery capabilities. Addepto also develops its own product, ContextClue, and contributes open-source solutions, recognized by Forbes as a top AI consulting company.

• At least 5 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 with experience in performance tuning, query optimization, and data warehousing solutions.
• Experience designing and implementing data governance and data management processes.
• Expertise in Big Data technologies including Apache Airflow, Dagster, Databricks, Spark, and DBT.
• Experience deploying solutions in cloud environments, preferably Azure.
• Knowledge in building and deploying Power BI reports and dashboards for data visualization.
• Excellent understanding of dimensional data and data modeling techniques.
• Consulting experience guiding clients on architecture, 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 fields.

Nice to have:

• Experience with CI/CD processes.
• Familiarity with Kubernetes, Kafka, Power BI, Dagster, and 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 and performance.
• Lead development of CI/CD and MLOps processes to automate deployments and monitoring.
• Develop and maintain applications for aggregating, processing, and analyzing diverse data sources.
• Collaborate with Data Science teams on Machine Learning projects including 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 with optimal data quality.
• Ensure data security, compliance, and governance best practices across all data pipelines.

Projects:

• Design and development of a universal data platform for global aerospace companies using Azure and Databricks.
• Data platform transformation for an energy management association leveraging Databricks and Apache Spark/PySpark.
• Design of data transformation and data ops pipelines for a global car manufacturer including real-time streaming and batch data processing.