Senior Databricks Platform Engineer

Wipro; Bengaluru, Mumbai, Chennai; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Wipro is seeking a Senior Databricks Platform Engineer to design and scale a next‑generation data platform supporting analytics, AI, governance, and self‑service data consumption.

You will engineer reusable platform capabilities, enable enterprise‑scale governance, improve observability, and drive operational excellence across the Databricks ecosystem while collaborating with cross‑functional teams.

Qualifications

• Extensive experience building data platforms on Databricks.
• Strong SQL & PySpark skills.
• Experience with Unity Catalog and data governance.
• Knowledge of Delta Lake and Medallion architecture.
• Experience with CI/CD and IaC.
• Exposure to cloud platforms (AWS/GCP/Azure).
• Knowledge of data quality, observability, and data lineage.

Responsibilities

• Design scalable data pipelines on Databricks using PySpark, SQL, and Delta Lake.
• Develop CDC, batch, and streaming ingestion for enterprise workloads.
• Implement and manage Medallion Architecture (Bronze/Silver/Gold).
• Develop governance solutions with Unity Catalog including masking and access controls.
• Build data quality, monitoring, and observability frameworks.
• Implement CI/CD pipelines using Databricks Asset Bundles, Git, and IaC.
• Optimize Databricks clusters and SQL Warehouses for performance and cost.
• Enable self-service analytics via semantic layers and governed datasets.
• Collaborate with platform, security, analytics, and business teams.

Skills

Databricks Lakehouse Platform

Unity Catalog

Delta Lake

Databricks SQL

PySpark

Advanced SQL

Data Modeling

CDC Architectures

ETL/ELT Frameworks

Real-Time Data Processing

Structured Streaming

Git

CI/CD

Terraform

Cloud Platforms (AWS/GCP/Azure)

Row-Level Security

Tools

Terraform

Git

dbt

Kafka

Airflow

Job description

Role & responsibilities

About the Role

Highly skilled Senior Databricks Platform Engineer to help build and scale a next-generation data platform supporting analytics, AI, governance, and self-service data consumption. The role focuses on engineering reusable platform capabilities, enabling enterprise-scale governance, improving observability, and driving operational excellence across the Databricks ecosystem.

Key Responsibilities

• Design and develop scalable data pipelines using Databricks, PySpark, SQL, and Delta Lake.
• Build CDC, batch, and streaming ingestion frameworks for enterprise-scale workloads.
• Implement and manage Medallion Architecture (Bronze, Silver, Gold).
• Develop governance solutions using Unity Catalog, including row-level security, data masking, and fine-grained access controls.
• Build and maintain Data Quality, Monitoring, and Observability frameworks.
• Implement CI/CD pipelines using Databricks Asset Bundles (DABS), Git, and Infrastructure as Code.
• Optimize Databricks clusters, SQL Warehouses, and workloads for performance and cost efficiency.
• Enable self-service analytics through semantic layers, metric views, governed datasets, and certified data products.
• Partner with platform, security, analytics, and business teams to drive adoption of Databricks capabilities.
• Participate in architecture discussions, platform modernization initiatives, and stakeholder workshops.

Required Skills

Databricks & Lakehouse

• Databricks Lakehouse Platform
• Delta Lake
• Unity Catalog
• Databricks Workflows
• Auto Loader
• Structured Streaming
• Databricks SQL

Data Engineering

• PySpark
• Advanced SQL
• Data Modeling
• ETL/ELT Frameworks
• CDC Architectures
• Real-Time Data Processing

Governance & Quality

• Row-Level Security
• Data Masking
• Data Lineage
• Data Quality Frameworks

Cloud & DevOps

• AWS/ GCP / Azure
• Git , CI/CD
• Terraform (nice to have)

Preferred Skills (These are not a must, nice to have)

• Scala
• dbt
• Kafka
• Airflow
• GenAI / AI Agents
• Enterprise Observability Solutions