Senior Databricks Engineer
Role Overview
As a Senior Databricks Engineer, you won't just be writing code; you will be the architect of a Databricks-Ready GTM engine. You will partner with industry-leading brands to design and implement scalable Lakehouse architectures that turn raw data into actionable AI-led innovation. This role is for a technical leader who wants to move beyond execution and into a space of strategic influence and human-centric engineering.
Key Responsibilities
Architecting Excellence: Design, develop, and optimize end-to-end data pipelines and Lakehouse architectures within the Databricks ecosystem.
Ecosystem Integration: Collaborate with Cloud Ops and Sales teams to ensure the technical engine supports faster co-selling and pipeline growth.
Performance Engineering: Manage and tune Spark clusters to ensure high-performance data processing and cost-efficiency.
Strategic Advisory: Act as a subject matter expert for clients, translating complex business requirements into robust technical roadmaps.
Mentorship: Lead a culture of "unrestricted growth" by mentoring junior engineers and advocating for best practices in Data & AI.
Technical Stack and Requirements
Primary Expert: 5+ years of experience in Data Engineering with a heavy focus on Databricks (Delta Lake, Unity Catalog, Photon)
Languages: Mastery of Python, SQL, and Scala/Spark
Cloud Infrastructure: Deep familiarity with AWS or Azure cloud-native environments
CI/CD: Experience with Terraform and automated deployment pipelines for data infrastructure
Certifications: Databricks Certified Data Engineer Professional (highly preferred)
Join Databricks Teams Built for Real Impact
Explore carefully selected roles within Databricks-aligned partners and organisations — where growth plans are clear, delivery expectations are real, and senior talent is trusted to make an impact.
