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Capgemini
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Data Engineer

Data Engineer

Capgemini

55 years

0 Lacs

bengaluru karnataka india

Posted:4 days ago| Platform:

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Skills Required

data collaborative technology drive design azure hadoop spark etl devops analytics architecture vault indexing orchestration adf databricks kafka engineering apache scala python sql strategies hive airflow reliability github terraform git configuration collaboration training certifications software development consulting strategy

Work Mode

On-site

Job Type

Full Time

Job Description

Long DescriptionRole: Data EngineerLocation: BangaloreExperiance: 9 to 12Choosing Capgemini means choosing a place where you’ll be empowered to shape your career, supported by a collaborative global community, and inspired to reimagine what’s possible. Join us in helping leading Consumer Products and Retail Services (CPRS) organizations unlock the value of technology and drive scalable, sustainable growth.

Role Overview

We are seeking a hands-on Data Engineer to design, build, and maintain scalable, reliable, and high-performance data pipelines on Microsoft Azure and big data ecosystems (Hadoop/Spark). You’ll work across ETL/ELT, dimensional modeling, data warehousing, data quality, and DevOps for data, enabling business intelligence, advanced analytics, and data science use cases at production scale.

Key Responsibilities

Data Architecture & Modeling

Design dimensional models (star/snowflake), data vault (nice-to-have), and canonical data models for analytics and BI.
Build and maintain enterprise data warehouses and data lakes/lakehouses with partitioning, indexing, and cost/performance optimization.

Pipelines & Orchestration

Develop robust ETL/ELT pipelines using Azure Data Factory (ADF), Databricks, Spark, and SQL.
Implement batch and streaming data ingestion (e.g., Kafka/Event Hubs) with parallel computing and checkpointing.
Build reusable frameworks for ingestion, transformation, and data quality validations.

Big Data Engineering

Optimize Apache Spark jobs (in Scala/Python/SQL): caching, partitioning, join strategies, AQE, and cost-aware design.
Manage Hadoop ecosystem components (HDFS, Hive/HCatalog, Oozie/Airflow, Ranger/Atlas basics).

Cloud, DevOps & Reliability

Implement data solutions on Azure (ADLS Gen2, ADF, Databricks, Synapse, Azure SQL/MI, Functions, Key Vault, Monitor/Log Analytics).
Apply DevOps practices: CI/CD (e.g., GitHub Actions/Azure DevOps), IaC (Bicep/Terraform), version control (Git), and configuration management.

What You’ll Love About Working Here

Flexible work options and a culture that values collaboration and continuous learning.
Opportunities to work on diverse projects and technologies.
Access to training and certifications in software development and emerging technologies.
Inclusive and supportive teams focused on innovation and excellence.

About Us

Capgemini is a global leader in consulting, technology services, and digital transformation. We help organizations accelerate their business transformation through innovative solutions. With a strong heritage and deep industry expertise, Capgemini is trusted by clients worldwide to deliver end-to-end services across strategy, design, and operations.Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transformation to address the evolving needs of customers and citizens. With a strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs—from strategy and design to operations.

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Data Engineer