DataBricks - Data Engineering

Role Purpose

The purpose of this role is to facilitate application solutions by developing and  reviewing module-level codes, creating replication patterns, performing root cause analysis to identify recurring issues and collaborating with internal and external stakeholders to ensure stable, well-documented deliverables that meet business objectives. 

About the Role

Senior Databricks Platform Engineer

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

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

·        Scala

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

Mandatory Skills: DataBricks - Data Engineering .

Experience: 5-8 Years .

Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.

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.