DGS India - Pune - Indiqube Orchid / Technology

Merkle Inc.; Pune District; Presencial; INR 2 500 000 - 4 000 000; Tempo integral

Resumo da oferta

Merkle Inc. in Pune seeks a hands-on Senior Data Engineer – AWS to build and maintain scalable data platforms on AWS. This IC role focuses on data pipeline development, cloud data engineering, and analytics enablement, requiring strong AWS data services, SQL, and Python expertise.

You will design batch and streaming pipelines, implement ingestion with S3, Glue, and EMR, and collaborate with architects, DevOps, and stakeholders to deliver secure, reliable, and cost-efficient data solutions.

Qualificações

• Strong SQL skills required, with complex queries and transformations.
• Experience with large datasets in Redshift / Athena.
• Hands-on AWS data services experience (S3, Glue, EMR).
• Design cloud-native data lakes and data warehouses.
• Experience with batch and streaming data pipelines.
• Knowledge of schema evolution and data quality checks.
• Proficient in Python for data engineering/ETL.
• Experience with PySpark/Spark is a plus.
• DevOps basics: IaC, CI/CD for data workloads.
• Collaborates with architects, DevOps, QA, business stakeholders.
• Awareness of cost optimization and security best practices.

Responsabilidades

• Design and build scalable ETL / ELT pipelines on AWS
• Develop SQL-based data transformations and Python pipelines
• Implement data ingestion pipelines using AWS services such as S3, Glue, EMR
• Build data models optimized for analytics, performance, and cost efficiency
• Monitor pipeline performance, reliability, and data quality
• Troubleshoot data pipeline issues and perform root‑cause analysis
• Apply best practices for security, reliability, and scalability
• 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

Conhecimentos

SQL

Python

Spark / PySpark

ETL / ELT

Data lake design

Data warehouse design

CI/CD for data

Terraform / CloudFormation

Data quality checks

Monitoring with CloudWatch

Formação académica

Bachelor’s or Master Degree

Ferramentas

Amazon S3

AWS Glue

Amazon Athena

Amazon Redshift

Amazon EMR

Descrição da oferta de emprego

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

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

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