Senior Databricks Data Engineer

EPAM Systems; Lavamünd; Vor Ort; EUR 127.000 - 190.000; Vollzeit

Zusammenfassung

EPAM Systems is seeking a Senior Databricks Data Engineer to join a Geneva or Zürich based team, with occasional onsite visits to the client’s Geneva office. You will drive onboarding of new datasets and pipelines into an enterprise Databricks Lakehouse platform, supporting critical data platform modernization programs.

You will collaborate with business and technical stakeholders to develop robust data ingestion, transformation and processing solutions while ensuring architectural best

Qualifikationen

• 5+ years of data engineering experience in enterprise-scale environments.
• Hands-on Databricks and Delta Lake experience for large-scale processing.
• Proficiency in Python and SQL for data transformations.
• Knowledge of Azure data services and cloud ecosystems.

Aufgaben

• Build and optimize data pipelines and ingestion flows into the Databricks platform.
• Analyze source systems, data models and define business transformation logic.
• Implement and maintain Medallion architecture (Bronze/Silver/Gold layers).
• Support migration of workloads from legacy data warehouses to Databricks.
• Troubleshoot performance, integration and pipeline failures in complex environments.
• Collaborate with technical and business teams to develop and deliver new data products.
• Produce documentation and deliver knowledge transfer sessions for client teams.

Kenntnisse

Databricks

Delta Lake

Python

SQL

Lakehouse architecture

Medallion design

ETL pipelines

Azure data services

Data governance

Communication

Jobbeschreibung

We're looking for a Senior Databricks Data Engineer to join our team in Geneva or Zürich, Switzerland , with occasional onsite visits to the client’s office in Geneva. In this role, you will drive onboarding of new datasets and pipelines into an enterprise Databricks Lakehouse platform and support critical data platform modernization programs . You will collaborate with business and technical stakeholders to develop robust data ingestion, transformation and processing solutions while ensuring architectural best practices, performance and compliance across multiple environments.

Responsibilities

• Build and optimize data pipelines and ingestion flows into the Databricks platform
• Analyze source systems, data models and define business transformation logic
• Implement and maintain Medallion architecture (Bronze/Silver/Gold layers)
• Support migration of workloads from legacy data warehouses to Databricks
• Troubleshoot performance, integration and pipeline failures in complex environments
• Collaborate with technical and business teams to develop and deliver new data products
• Produce documentation and deliver knowledge transfer sessions for client teams

Requirements

• 5+ years of data engineering experience in enterprise-scale environments
• Proven hands-on experience with Databricks and Delta Lake for large-scale processing
• Advanced programming in Python and SQL for data transformation workflows
• Expertise in Lakehouse architecture and Medallion design patterns
• Experience designing ETL pipelines and migrating workloads from data warehouses
• Familiarity with Azure-based data services and cloud ecosystems
• Knowledge of data governance and metadata best practices
• Strong communication skills with ability to manage multiple stakeholders
• Domain exposure to financial services or regulated industries is a plus