Data Engineer

Job Description:

Job Description – Data Engineer (AWS)

1. Basic Information

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

2. 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.

3. 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

4. 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

5. 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

6. Education Qualification

• •Bachelor’s or Master’s degree (or equivalent) in:
• •Computer Science
• •Information Technology
• •Data Engineering
• •or related field

7. 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