Data Engineer

dentsuaegis; Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Merkle in Mumbai seeks a hands-on Data Engineer (AWS) with 3–7 years of experience to develop scalable data platforms, build ETL/ELT pipelines, and enable analytics. You will work on AWS S3, Glue, Athena, Redshift, and EMR, with strong SQL and Python skills.

Collaboration with global teams and a focus on data quality are essential. The role requires design of cloud-native data lakes and warehouses, understanding batch/streaming concepts, and exposure to DevOps basics and cost optimization.

Qualifications

• Hands-on experience with AWS data services and Python for ETL/ELT
• Strong SQL skills with large datasets in Redshift/Athena
• Experience building batch and streaming pipelines
• Knowledge of data lakes and data warehouse architectures
• Experience with Spark / PySpark and structured data
• Familiarity with Terraform/CloudFormation and CI/CD for data workloads
• Good communication and collaboration with stakeholders

Responsibilities

• Design and build scalable ETL/ELT pipelines on AWS
• Develop SQL-based data transformations and Python-based pipelines
• Implement data ingestion using S3, Glue, and EMR
• Build analytics-ready data models for performance and cost efficiency
• Monitor pipeline performance, reliability, and data quality
• Collaborate with architects, DevOps, QA, and product teams
• Contribute to documentation, code reviews, and best practices

Skills

AWS

SQL

Python

S3

Glue

Athena

Redshift

EMR

Data modeling

Transformations

Performance tuning

Spark / PySpark

Terraform

CloudFormation

CI/CD for data workloads

AWS CloudWatch

Communication

Collaboration

Education

Bachelor's or Master's in CS/IT/Data Engineering

Tools

Snowflake

Job description

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
• 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