Data Engineer

Dentsu -
Goregaon, Mumbai, Maharashtra

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Job details

Full-time
4 days ago

Qualifications

CI/CD
Performance tuning
Data modelling
Computer Science
DevOps
Spark
Master's degree
SQL
AWS
Bachelor's degree
Terraform
Continuous integration
EMR systems
ETL
Agile
S3
Kafka
Metadata
Redshift
AI
Communication skills
Data warehouse
Python
AWS Certified Solutions Architect – Professional
Information Technology

Full job description

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

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