Data Engineer

Dentsu Global Services; Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Merkle is seeking a hands-on Data Engineer – AWS in Mumbai to design, build and maintain scalable data pipelines. You will work on AWS data services, SQL and Python to deliver batch and streaming solutions in a global delivery setup.

The role requires 3–7 years of hands-on experience, strong data modeling, and collaboration with architects, DevOps and BI teams. Permanent, full-time position in Mumbai with opportunities to work on cutting-edge cloud data platforms.

Qualifications

• Bachelor's or Master's degree in a relevant field (CS/IT/Data Eng).
• Hands-on experience with AWS data services (S3, Glue, Athena, Redshift, EMR).
• Strong SQL and Python skills with experience in data pipelines and data modeling.

Responsibilities

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

Skills

AWS Data Engineering

SQL

Python

PySpark

Spark

Data Modeling

Data Quality

CI/CD

Terraform / CloudFormation

Education

Bachelor's or Master's in Computer Science/IT/Data Engineering

AWS Certifications (Solutions Architect, DevOps Professional)

Snowflake Core Certification (optional)

Tools

AWS S3, Glue, Athena, Redshift, EMR

Terraform / CloudFormation

CI/CD tools

AWS CloudWatch

Spark / PySpark

Job description

Job Description:

Job Description – Data Engineer (AWS)

Basic Information

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

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.

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‑H​ave 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

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

Requirements: