Databricks Platform Engineer

Experience:

3 to 6 years

Notice Period:

Immediate to 15 days

Location:

Bangalore

Work from office

JOB DESCRIPTION

Job Description: Databricks Platform Engineer / Administrator (AWS)

Department: Data Engineering / Cloud Platform / DevOps

About the Role

We are looking for a skilled and proactive 
Databricks Platform Engineer / Administrator

to manage, optimize, and govern our Databricks environment on AWS. The ideal candidate will be responsible for overseeing platform operations, optimizing performance and cost, and ensuring secure and efficient use of Databricks and integrated AWS services.

This role sits at the intersection of platform engineering, data infrastructure, and cost governance, requiring both technical depth and cross-functional collaboration.

Key Responsibilities

Platform Administration

• Deploy, configure, and manage 
  Databricks workspaces

on AWS.
- Set up and maintain 
AWS infrastructure

(VPCs, IAM roles, S3, security groups) to support Databricks operations.
- Manage user access, job permissions, cluster configurations, and workspace-level controls.

Cost Optimization

• Implement and enforce 
  cluster policies

to control resource consumption and prevent cost overruns.
- Promote efficient compute usage by enabling 
job clusters

, 
auto-termination

, and 
spot instance

strategies.
- Monitor and analyze cost using 
AWS Cost Explorer

, 
Databricks REST APIs

, and internal dashboards.
- Optimize storage costs through 
S3 lifecycle policies

, 
Delta Lake optimization

, and 
table version management

.

Performance Tuning

• Analyze and tune 
  Spark job performance

, including partitioning, caching, and join strategies.
- Provide guidance on using 
Photon runtime

, 
Delta Live Tables

, and 
SQL optimization best practices

.
- Collaborate with data engineers and analytics teams to improve job execution efficiency and pipeline throughput.

Monitoring & Observability

• Set up and manage 
  logging, monitoring, and alerting

via CloudWatch, Databricks audit logs, and external tools.
- Track metrics such as cluster utilization, job failures, job durations, and resource bottlenecks.
- Develop dashboards for real-time visibility into platform usage, performance, and cost.

Security & Governance

• Enforce access control through 
  Unity Catalog

, 
IAM roles

, and 
cluster policies

.
- Ensure compliance with enterprise security policies, data governance standards, and audit requirements.
- Prevent data duplication and misuse through strong access boundaries and usage monitoring.

Automation & Documentation

• Automate provisioning and configuration using 
  Terraform

, 
Databricks CLI

, and 
REST APIs

.
- Maintain detailed documentation of cluster policies, platform standards, optimization playbooks, and cost governance guidelines.
- Drive platform standardization and advocate for best practices across teams.

Qualifications

Required

• 3–6+ years of experience managing 
  Databricks on AWS

or similar Spark-based platforms.
- Strong hands-on experience with 
AWS services

(S3, IAM, VPC, EC2, CloudWatch).
- Proficiency in 
Spark performance tuning

and 
Databricks architecture

.
- Solid understanding of 
cost optimization strategies

in cloud-based data platforms.
- Experience with 
Databricks cluster policies

, 
job scheduling

, and 
Delta Lake

.
- Familiarity with 
Python, SQL, Terraform

, and 
Databricks REST APIs

.

Preferred

• Experience with 
  Unity Catalog

, 
Delta Live Tables

, or 
MLflow

.
- Knowledge of 
AWS cost governance tools

(Cost Explorer, Budgets, Trusted Advisor).
- Prior work in FinOps, DataOps, or Cloud Center of Excellence (CCoE) roles.
- Certifications such as:
- Databricks Certified Data Engineer / Admin
- AWS Certified Solutions Architect / DevOps Engineer