Data Engineer

Dentsu; Pune District; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Merkle is seeking a hands-on Data Engineer to design, develop, and maintain scalable data platforms on AWS. The role focuses on end-to-end data pipelines, analytics enablement, and data lake/warehouse architectures in a global delivery setting.

You will work with S3, Glue, Redshift, and EMR, applying strong SQL and Python skills to build reliable batch and streaming pipelines. The position is based in Pune with IST shift timings.

Qualifications

• Hands-on experience with AWS data services and Python/SQL.
• Strong experience designing batch/streaming data pipelines.
• Experience building cloud-native data lakes and data warehouses.

Responsibilities

• Design and build scalable ETL/ELT pipelines on AWS.
• Develop SQL-based transformations and Python-based pipelines.
• Implement data ingestion using S3, Glue, and EMR.
• Build data models optimized for analytics, performance, and cost.
• Support deployment and execution of pipelines across environments.
• Monitor pipeline performance, reliability, and data quality.
• Collaborate with architects, DevOps, QA, and stakeholders.

Skills

AWS Cloud

SQL

Python

PySpark

Spark

Data Pipelines

ETL/ELT

Data Modeling

Data Lakes

Batch/Streaming

Education

Bachelor’s or Master Degree

AWS Certified Solutions Architect – Professional

Snowflake Core

Tools

Amazon S3

AWS Glue

Amazon Athena

Amazon Redshift

Amazon EMR

Terraform

CloudFormation

Job description

Job Description:

Job Description

Details

Project Details

Comments

Business Title

Data Engineer

Years of Experience

Min 3 and max upto 7.

Job Descreption

Looking for a hands‑on Senior Data Engineer – AWS with experience to development, build, and maintain 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 role requires strong hands‑on skills in AWS data services, SQL, and Python, along with experience building reliable batch and streaming data pipelines in a global delivery environment.

Must have skills

• Cloud & Data Engineering (AWS)
• Strong hands‑on experience with AWS data services, including:
• - 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 pipelines and basic exposure to streaming concepts
• SQL & Python (Mandatory)
• Strong SQL skills (mandatory)
• Writing 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 is a strong plus
• Good understanding of data modeling, transformations, and performance tuning
• Data Processing & Engineering
• Hands‑on experience with distributed data processing frameworks (Spark / PySpark)
• Experience handling structured and semi‑structured data
• Understanding of schema evolution, data quality checks, and validation logic
• DevOps & Platform Basics
• Working knowledge of Infrastructure as Code (Terraform and/or CloudFormation)
• Basic experience with CI/CD pipelines for data workloads
• Understanding of logging and monitoring using CloudWatch
• Collaboration
• Ability to work closely with architects, DevOps, QA, and business stakeholders
• Good communication skills to explain technical concepts clearly

Good to have skills

• Exposure to streaming technologies such as Amazon Kinesis or Kafka
• Familiarity with Lakehouse and modern data platform patterns
• Experience integrating AWS data platforms with BI / reporting tools
• Basic knowledge of data governance, data quality, and metadata concepts
• Awareness of AWS cost optimization best practices
• Experience working in Agile delivery models, with global clients
• Exposure to AI / ML

Key responsibiltes

• Data Engineering & Development
• Design and build scalable ETL / ELT pipelines on AWS
• Develop SQL‑based data transformations and Python‑based data pipelines
• Implement data ingestion pipelines using AWS services such as S3, Glue, EMR
• Build data models optimized for analytics, performance, and cost efficiency
• Platform & Operations
• Support deployment and execution of data pipelines across environments
• Monitor pipeline performance, reliability, and data quality
• Troubleshoot data pipeline issues and perform root‑cause analysis
• Apply best practices for security, reliability, and scalability
• Collaboration & Delivery
• Work closely with architects and product teams to understand requirements
• Translate business and analytics needs into working AWS data solutions
• Contribute to documentation, code reviews, and engineering standards

Education Qulification

• 1. Bachelor’s or Master Degree or equivalent Degree

Certification If Any

• 1.AWS Certified Solutions Architect / DevOps – Professional
• 2. Snowflake Core

Shift timing

12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone

Location:

DGS India - Pune - Indiqube Orchid

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent