Databricks Platform Engineer

We are hiring a Databricks Platform Engineer

Description

Are you passionate about building enterprisegrade data platforms that power both advanced analytics

and nextgeneration Agentic AI solutions?

Join us as a Databricks Platform Engineer, where you will play a key role in engineering, scaling, and

operating our enterprise Databricks platform across a highly regulated, multicloud environment. You will

enable data engineers, AI/ML teams, and downstream platform consumers by building a secure,

automated, and wellgoverned data foundation.

In this role, you will work at the intersection of data engineering, platform engineering, and AI

enablement.

You will design and automate cloud-native platform components, implement governance frameworks,

optimize performance, and ensure compliance with strict security and dataprivacy requirements.

What you do

Platform Engineering & Operations

• Engineer, deploy, and operate Databricks workspaces, clusters, jobs, and ML runtimes

across Azure, AWS, and multi-cloud architectures.

• Build and manage automated CI/CD pipelines, infrastructure-as-code (IaC), and platform lifecycle

processes (provisioning, scaling, upgrades).

• Ensure platform reliability, observability, and cost efficiency through proactive monitoring, tuning,

and optimization.

Data Platform & AI Enablement

• Enable scalable data ingestion, transformation, and processing pipelines using Delta Lake, Unity

Catalog, and Databricks Jobs/Workflows.

• Collaborate with AI/ML teams to support feature stores, model training pipelines, and data

services powering Agentic AI use cases.

• Implement and maintain enterprise-wide metadata, lineage, and data quality controls.

Governance, Security & Compliance

• Ensure strong security baselines, including Identity & Access Management (IAM), network

isolation, data encryption, secret management, and secure cluster configurations.

• Implement governance guardrails aligned with regulatory, compliance, and risk frameworks (e.g.,

GDPR, financial regulations).

• Enforce platform standards, policies, cluster controls, and workspace configurations across

Operating Entities.

Automation & Tooling

• Build reusable automation components, templates, and frameworks for platform onboarding and

daytoday operations.

• Support the development of monitoring dashboards, alerting systems, and platform health

indicators.

Collaboration & Support

• Work with data engineers, data scientists, AI architects, cloud teams, and security teams to

ensure seamless integration of Databricks with enterprise data and AI ecosystems.

• Troubleshoot platform issues and support stakeholders in building robust, scalable workloads.

• Contribute to platform documentation, best practices, and engineering playbooks.

What you bring

• Hands-on engineering experience with Databricks in enterprise environments (Azure or AWS;

multi-cloud preferred).

• Strong understanding of Delta Lake, Unity Catalog, cluster architectures, Databricks

Jobs/Workflows, and ML runtimes.

• Solid expertise in IaC tools such as Terraform, Pulumi, or ARM/Bicep, and CI/CD platforms such

as GitHub Actions, Azure DevOps, or GitLab.

• Deep knowledge of data platform architecture, including ingestion pipelines, ETL/ELT patterns,

data governance, lineage, and data quality frameworks.

• Experience operating platforms in regulated, security-sensitive industries, ensuring

compliance and strong platform governance.

• Familiarity with enabling AI/ML workloads, data products, feature engineering, or MLOps

pipelines.

• Strong grounding in cloud-native engineering, distributed systems, and event-driven

architectures.

• Ability to work collaboratively across cross-functional engineering, cloud, security, and AI teams.