DataBricks - Data Engineering

Job description:
Job Description 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.
J͏ob Role:-
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.
S͏kills:-
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
Nice to have: -
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.
Profile description:
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.

Skills
Databricks

Experience
5-8 yrs