Databricks Data Platform Engineer

Job summary

The Databricks Data Platform Engineer role involves designing, operating, and enhancing enterprise-grade data platforms using Databricks in an Azure cloud environment. Key responsibilities include developing platform components, automating provisioning with Infrastructure as Code, enabling self-service capabilities, and providing technical guidance to data teams while promoting best practices for data ingestion and analytics.

Benefits

Qualifications

• 5+ years of experience in data platform engineering or data engineering in large-scale enterprise environments
• Hands-on experience with Databricks (data engineering, analytics, or platform administration)
• Proficient in Python and SQL, and familiar with CI/CD practices
• Solid understanding of data lake/lakehouse architectures, data ingestion and transformation patterns, and cloud-native data platforms
• Comfortable working in an agile (Scrum) environment
• Clear communication and collaboration with both technical and non-technical stakeholders
• Strong enablement mindset and enjoy helping others succeed

Responsibilities

• Design, build, and operate scalable and secure Databricks data platforms in a cloud environment (Azure-based)
• Develop and maintain shared platform components, including workspace standards, cluster policies, networking, and integrations
• Automate platform provisioning and configuration using Infrastructure as Code and CI/CD pipelines
• Ensure platform reliability, performance, cost-efficiency, and observability
• Enable self-service data engineering and analytics capabilities by providing reusable templates, libraries, and reference architectures
• Define and promote platform standards, guardrails, and best practices for data ingestion, transformation, and analytics on Databricks
• Support teams in adopting these standards while balancing autonomy and governance
• Actively remove friction for data teams by improving developer experience on the platform
• Act as a trusted technical advisor for data engineers, analytics engineers, data scientists, and product teams
• Support domain teams in designing and implementing data pipelines and analytical use cases on Databricks
• Partner with architects, security, and governance teams to ensure platform solutions align with enterprise policies
• Translate business and analytical requirements into robust, scalable technical solutions
• Contribute to and deliver training sessions, workshops, and onboarding materials for Databricks users
• Coach and mentor engineers and analysts to raise overall data platform maturity
• Share knowledge through documentation, internal communities, and data engineering guilds
• Actively contribute to a strong Data & AI engineering culture within the organization

Skills

Certifications

Degrees

Relocation