Data Engineer

Dentsu Global Services; Mumbai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Dentsu Global Services in Mumbai is seeking a hands-on Data Engineer – AWS with 3 to 7 years of experience to design and build scalable, secure data platforms on AWS. This individual contributor role focuses on data pipeline development, cloud data engineering, and analytics enablement.

You will work with AWS data services, SQL, Python, and PySpark to create reliable batch and streaming pipelines, implement data ingestion with S3/Glue/EMR, and collaborate with architects and product teams to

Qualifications

• 3–7 years of hands-on data engineering experience.
• Strong SQL skills and Python for ETL/ELT.
• Experience with AWS data services (S3, Glue, Athena, Redshift, EMR).
• Knowledge of batch and streaming data pipelines.
• Experience in data modeling, data quality checks, and validation logic.
• Familiarity with CI/CD for data workloads and IaC concepts.

Responsibilities

• Design and build scalable ETL/ELT pipelines on AWS.
• Develop SQL- and Python-based data transformations.
• Implement data ingestion using S3, Glue, and EMR.
• Construct data models optimized for analytics, performance, and cost.
• Monitor pipeline performance, reliability, and data quality.
• Collaborate with architects, DevOps, QA, and stakeholders.

Skills

SQL

Python

Spark / PySpark

AWS data services

Data modeling

Data quality checks

ETL/ELT design

Batch processing

Streaming pipelines

CI/CD

Terraform

CloudWatch

Education

Bachelor’s or Master’s degree in Computer Science or Information Technology

AWS Certifications (Preferred)

Snowflake Core Certification (optional)

Tools

Amazon S3

AWS Glue

Amazon Athena

Amazon Redshift

Amazon EMR

Terraform / CloudFormation

SageMaker / AI/ML (optional)

Job description

• Data quality checks

Job Description – Data Engineer (AWS)

We are looking for a hands-on Data Engineer – AWS with 3 to 7 years of experience in developing, building, and maintaining scalable, secure, and high-performance data platforms on AWS.

This is an individual contributor role focused on data pipeline development, cloud data engineering, and analytics enablement. The candidate should have strong hands‑on expertise in AWS data services, SQL, and Python, along with experience in building reliable batch and streaming pipelines in a global delivery environment.

Basic Information

• Job Title: Data Engineer (AWS)
• Experience: 3 to 7 Years
• Role Overview

Cloud & Data Engineering (AWS)

• Strong hands‑on experience with:
• Amazon S3
• AWS Glue
• Amazon Athena
• Amazon Redshift
• Amazon EMR
• Experience designing cloud-native data lakes and data warehouse architectures
• Solid understanding of batch data processing and basic exposure to streaming concepts

SQL & Python (Mandatory)

• Strong SQL skills (mandatory):
• Complex queries, joins, aggregations, and transformations
• Experience working with large datasets in Redshift/Athena
• Strong Python skills (mandatory):
• Python for data engineering and ETL use cases
• Experience with PySpark / Spark (preferred)
• Good understanding of:
• Data modeling
• Transformations
• Performance tuning

Data Processing & Engineering

• Hands‑on experience with Spark / PySpark
• Experience handling:
• Structured and semi‑structured data
• Knowledge of:
• Schema evolution
• Data quality checks
• Validation logic

DevOps & Platform Basics

• Working knowledge of Infrastructure as Code (Terraform / CloudFormation)
• Basic experience with CI/CD pipelines for data workloads
• Understanding of logging and monitoring using AWS CloudWatch

Collaboration

• Ability to work with architects, DevOps, QA, and business stakeholders
• Good communication skills to clearly explain technical concepts

Good-to-Have Skills

• Experience with streaming technologies (Amazon Kinesis / Kafka)
• Familiarity with Lakehouse and modern data platform architectures
• Integration experience with BI / reporting tools
• Basic knowledge of:
• Data governance
• Data quality
• Metadata management
• Awareness of AWS cost optimization (FinOps basics)
• Experience in Agile delivery models with global teams
• Exposure to AI / ML use cases
• Key Responsibilities

Key Responsibilities

Data Engineering & Development

• Design and build scalable ETL/ELT pipelines on AWS
• Develop:
• SQL-based data transformations
• Python-based data pipelines
• Implement data ingestion pipelines using S3, Glue, EMR
• Build data models optimized for analytics, performance, and cost efficiency

Platform & Operations

• Support deployment and execution of data pipelines
• Monitor:
• Pipeline performance
• Reliability
• Data quality
• Troubleshoot data issues and perform root cause analysis
• Apply best practices for:
• Security
• Reliability
• Scalability

Collaboration & Delivery

• Work with architects and product teams to understand requirements
• Translate business needs into AWS data engineering solutions
• Contribute to:
• Documentation
• Code reviews
• Engineering best practices

Education Qualification

• Bachelor’s or Master’s degree (or equivalent) in:
• Computer Science
• Information Technology
• Data Engineering
• or related field
• Certifications (Preferred)
• AWS Certified:
• Solutions Architect
• DevOps (Professional)
• Snowflake Core Certification (optional)

Location

DGS India - Mumbai - Goregaon Prism Tower

Brand

Merkle

Time Type

Full time

Contract Type

Permanent#DGS