Senior Data Engineer (Databricks)

About the role

Join a fast‑growing technology organization that is redefining productivity paradigms in the software engineering industry. You will design, develop, and optimise data pipelines on Databricks and Apache Spark for a banking environment.

Key responsibilities

• Design, develop and optimise data pipelines using Databricks, Apache Spark and Delta Lake.
• Build scalable ETL/ELT processes to ingest, transform and deliver data from various banking systems.
• Collaborate with data scientists, analysts and business stakeholders to understand data requirements.
• Optimise Databricks cluster configurations and query performance for cost efficiency.
• Implement security best practices and ensure compliance with PCI‑DSS, SOX and GDPR.

Required profile

• 5+ years of data engineering experience, with at least 3 years on the Databricks platform.
• Strong proficiency in Apache Spark (PySpark or Scala) and expert‑level SQL.
• Solid understanding of cloud platforms (AWS, Azure or GCP) and banking data regulations.
• Advanced English communication skills and strong problem‑solving ability.

Required skills

• Databricks (certified Data Engineer preferred)
• Apache Spark, PySpark, Scala
• Delta Lake and lakehouse architecture
• SQL, Python, Pandas, NumPy
• Kafka or Event Hubs for real‑time streaming
• Terraform or CloudFormation (IaC)
• CI/CD pipelines and DevOps practices
• Data governance tools

What we offer

• Opportunity to work on innovative projects with leading brands using the latest technologies.
• Membership in a multicultural community of tech experts.
• Flexible and fully remote working environment.
• Access to the #ParserCommunity and professional networking on LinkedIn.