Data Engineer - C

Capgemini; Hyderabad; On-site; INR 800,000 - 1,500,000; Full time

Job summary

A major IT consulting company is seeking a Data Engineer in Hyderabad, India. The successful candidate will build reliable and scalable data infrastructure and lead a team of data engineers. Responsibilities include ensuring technical excellence in data engineering projects and fostering collaboration with key stakeholders. Ideal candidates should have strong experience with AWS, GCP, and relevant data engineering tools and methodologies.

Qualifications

• Strong experience in data engineering roles with proficiency in data architecture.
• Experience with cloud platforms like AWS and GCP.
• Ability to lead teams and manage data engineering projects.

Responsibilities

• Build reliable and scalable data infrastructure.
• Lead and manage a team of data engineers.
• Ensure technical excellence and collaboration with stakeholders.

Skills

Ab Initio

Agile (Software Development Framework)

Apache Hadoop

AWS Airflow

AWS Athena

AWS Code Pipeline

AWS EFS

AWS EMR

AWS Redshift

AWS S3

Azure ADLS Gen2

Azure Data Factory

Azure Data Lake Storage

Azure Databricks

Azure Event Hub

Azure Stream Analytics

Bitbucket

Continuous Integration and Continuous Delivery (CI/CD)

Data Governance

Data Modeling

DevOps

GCP BigQuery

Git

Jenkins

Python

SQL

Talend

Job description

Data Engineer – Job Description

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Responsibilities

Leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high‑quality data solutions to support the organization's data‑driven objectives.

Qualifications & Skills

• Ab Initio
• Agile (Software Development Framework)
• Apache Hadoop
• AWS Airflow
• AWS Athena
• AWS Code Pipeline
• AWS EFS
• AWS EMR
• AWS Redshift
• AWS S3
• Azure ADLS Gen2
• Azure Data Factory
• Azure Data Lake Storage
• Azure Databricks
• Azure Event Hub
• Azure Stream Analytics
• Azure Sunapse
• Bitbucket
• Change Management
• Client Centricity
• Collaboration
• Continuous Integration and Continuous Delivery (CI/CD)
• Data Architecture Patterns
• Data Format Analysis
• Data Governance
• Data Modeling
• Data Validation
• Data Vault Modeling
• Database Schema Design
• Decision-Making
• DevOps
• Dimensional Modeling
• GCP Big Table
• GCP BigQuery
• GCP Cloud Storage
• GCP DataFlow
• GCP DataProc
• Git
• Google Big Tabel
• Google Data Proc
• Greenplum
• HQL
• IBM Data Stage
• IBM DB2
• Industry Standard Data Modeling (FSLDM)
• Industry Standard Data Modeling (IBM FSDM)
• Influencing
• Informatica IICS
• Inmon methodology
• JavaScript
• Jenkins
• Kimball
• Linux - Redhat
• Negotiation
• Netezza
• NewSQL
• Oracle Exadata
• Performance Tuning
• Perl
• Platform Update Management
• Project Management
• PySpark
• Python
• R
• RDD Optimization
• SantOs
• SaS
• Scala Spark
• Shell Script
• Snowflake
• SPARK
• SPARK Code Optimization
• SQL
• Stakeholder Management
• Sun Solaris
• Synapse
• Talend
• Teradata
• Time Management
• Ubuntu
• Vendor Management