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Protocol Intelligence
Data-driven signals on your job's competitivenessNiche Databricks skillset but mid-level Bangalore role increases applicant density moderately.
Specialized Databricks, Delta Lake, MLflow and MLOps expertise limits transferability across industries.
Mandatory 5+ years and 3+ years Databricks plus specific platform, IaC, and MLOps requirements enforce strict filtering.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, configure, automate, and operationalize the Databricks Lakehouse platform for enterprise-scale Data & AI solutions.
Establish scalable, secure, compliant, and high-availability environments supporting data engineering, AI/ML workflows, and platform governance.
Implement and manage CI/CD pipelines, infrastructure as code, monitoring, and support operational readiness and incident resolution for the Databricks platform.
Minimum Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, IT, or related field.
5+ years experience in Data, Platform, or Cloud Engineering, with 3+ years hands-on on Databricks Lakehouse Platform.
Proficiency in Delta Lake, Unity Catalog, MLflow, Structured Streaming, PySpark, Spark SQL, Python, SQL, and cloud platforms (Azure, AWS, or GCP).
Experience with DevOps practices including Infrastructure as Code (Terraform), CI/CD tools (GitHub Actions, Azure DevOps), and platform automation.
Ideal Candidate Profile
Experienced engineer capable of managing end-to-end Databricks platform engineering including automation, integration, security, and governance.
Comfortable working cross-functionally with architects, data scientists, AI engineers, security teams, and business stakeholders delivering enterprise Data & AI platforms.
Skilled in supporting scalable DataOps, MLOps, and AI/ML workloads, including generative AI and agent orchestration frameworks integration.