DataBricks - Data Engineering

Wipro; Bengaluru; Presencial; INR 3.500.000 - 5.500.000; Jornada completa

Descripción de la vacante

Wipro is seeking a Senior Databricks Platform Engineer to design and develop scalable data pipelines and governance solutions within a next-generation data platform. The role focuses on enterprise-scale ingestion, Medallion architecture, and self-service analytics.

You will collaborate with security, analytics, and business teams, optimize workloads, and contribute to platform modernization initiatives while enabling observability and cost efficiency across the Databricks ecosystem.

Formación

• Mandatory skills: Databricks - Data Engineering.
• 5-8 years of experience in data engineering or equivalent.
• Experience building scalable data platforms and pipelines.

Responsabilidades

• 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 IaC.
• 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.

Conocimientos

PySpark

Advanced SQL

Data Modeling

ETL/ELT Frameworks

CDC Architectures

Real‑Time Data Processing

Scala

dbt

Kafka

Airflow

GenAI / AI Agents

Enterprise Observability Solutions

Herramientas

Databricks Lakehouse Platform

Delta Lake

Unity Catalog

Databricks Workflows

Auto Loader

Structured Streaming

Databricks SQL

Descripción del empleo

Job Role:

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.

Job Description

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

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

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.

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