Senior Data Engineer – Databricks Specialist

About the role

We are seeking an experienced Senior Data Engineer with deep expertise in Databricks and Apache Spark. You will design, build, and maintain scalable data pipelines, data lakes, and Lakehouse solutions that power advanced analytics and data‑driven products across cloud environments.

Key responsibilities

• Own end‑to‑end data engineering features, architecture, and code quality.
• Design, implement, and maintain Databricks‑based pipelines and workflows.
• Build and optimise ETL/ELT processes using Spark on Databricks.
• Design and manage Delta Lake and Lakehouse architectures.
• Integrate diverse data sources and ensure reliable ingestion.
• Automate orchestration, scheduling, and monitoring of Databricks jobs.
• Implement fault‑tolerant, scalable processing workflows.
• Ensure high data quality, consistency, and accuracy.
• Make decisions on storage, compute, and performance optimisation.
• Collaborate with analytics, BI, and business stakeholders.

Required profile

• 7+ years of data engineering experience.
• Strong hands‑on experience with Databricks and Apache Spark.
• Proficiency in Python or Scala (both preferred).
• Solid knowledge of SQL, relational databases, and data‑warehousing concepts.
• Experience with ETL/ELT design and cloud platforms (Azure, AWS, or GCP).
• Familiarity with Unix‑like operating systems and version control.
• Excellent communication skills in English.

Required skills

• Databricks
• Apache Spark
• Python
• Scala
• SQL
• Delta Lake
• Azure
• AWS
• GCP
• ETL/ELT
• Data Lakes
• Lakehouse architecture
• Unix
• Git
• Kafka (streaming)
• Airflow (or Databricks Workflows)
• Docker
• Kubernetes