AWS Data Engineer

Important Note (Please Read Before Applying)

Do NOT apply if:

• You have less than 5 years or more than 10 years of total data engineering experience
• You do not have strong AWS data engineering experience
• You do not have hands-on Python for ETL/ELT
• You cannot work from the specified location (Hybrid role)
• You are on a notice period longer than 30 days
• Your background is unrelated (e.g., BI only, support, testing, non-cloud roles)

Apply ONLY if you meet ALL criteria above. Random or irrelevant applications will not be considered

Job Title: AWS Data Engineer

Location: Hyderabad

Experience: 6 +years

Employment Type: Permanent

Notice Period: Immediate Joiners Only

CTC: Up to 25 LPA

About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Job Description

We are seeking an experienced Senior Data Engineer to design, build, and optimize scalable, high-performance data platforms using AWS cloud services and Python.

The ideal candidate will architect end-to-end data pipelines, automate workflows, ensure data quality, and support advanced analytics and AI workloads across the organization.

This role requires deep expertise in AWS data services, modern data architecture, and Python-based data engineering, with a strong ability to deliver reliable, production-grade data solutions at scale.

Responsibilities

• Architect and implement scalable, fault-tolerant data pipelines using AWS Glue, Lambda, EMR, Step Functions, and Redshift
• Build and optimize data lakes & data warehouses on S3, Redshift, Athena
• Develop Python-based ETL/ELT frameworks and reusable transformation modules
• Integrate data from RDBMS, APIs, Kafka/Kinesis, SaaS systems into unified datasets
• Lead data modeling, schema design, partitioning, and performance optimization
• Ensure data quality, lineage, and observability using AWS Data Catalog, Glue Data Quality, or equivalent tools
• Define and enforce data governance, security, and compliance (IAM, encryption, access control)
• Collaborate with Data Science, Analytics, Product, and DevOps teams to support ML and BI workloads
• Implement CI/CD pipelines for data workflows using AWS CodePipeline, GitHub Actions, or Cloud Build
• Provide technical leadership, code reviews, and mentoring for junior engineers
• Monitor and optimize data infrastructure, troubleshoot failures, and lead capacity planning

Mandatory Skills

510 years of hands-on Data Engineering experience

Strong expertise in Python (pandas, PySpark, boto3, SQLAlchemy)

Deep experience with AWS Data Services:

AWS Glue, Lambda, EMR, Step Functions

DynamoDB, Redshift, Athena, S3

Kinesis, IAM, CloudWatch

Strong SQL, data modeling, performance tuning

Experience designing data lakes, data warehouses, streaming pipelines

Hands-on ETL/ELT development, partitioning, data validation

Experience with Git and CI/CD for data pipelines

Knowledge of containerization (Docker/Kubernetes) and DevOps basics