Data Engineer

Dentsu Aegis Network Ltd.; Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Merkle is seeking a hands-on Data Engineer – AWS in Mumbai to design, build and optimize scalable data pipelines. You will work on cloud-native data lakes and data warehouse architectures, using PySpark, SQL, and AWS services in a global delivery setting.

The role requires strong Python and SQL skills, experience with Spark, and familiarity with Terraform/CI/CD. You will collaborate with architects and product teams to translate business needs into scalable data solutions.

Qualifications

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

Responsibilities

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

Skills

AWS data services

SQL

Python

Spark/PySpark

Data modeling

Data pipelines

Cloud architecture

Communication

Education

Bachelor’s or Master’s degree in CS/IT/Data Engineering

Tools

Terraform

CloudFormation

CI/CD pipelines

AWS CloudWatch

Job description

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.

Must-Have Skills

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
• Aware of AWS cost optimization (FinOps basics)
• Experience in Agile delivery models with global teams
• Exposure to AI / ML use cases

Key Responsibilities

• 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
• 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

About dentsu

For over 120 years, innovation has been a core tenet of our offering – exploring new ways to reach, engage and nurture relationships with audiences. Together we drive a multiplier effect for clients at a global scale, through the development of Integrated Growth Solutions that are underpinned by our promise to clients: innovating to impact. Be a force for good. Sustainability is a vital part of our business and an important area of focus for our clients. We’re leading the way – helping to build a more sustainable planet. Dream loud. In this moment of transformation, we need our people to be fearless, embracing change and ambiguity, driven by the love for their work and excitement for the future. Team without limits. We create opportunities for connection and collaboration between our colleagues and clients, building a sense of belonging and having some fun along the way. Find out more about us Who we are Our Social Impact Our work