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 RedshiftBuild and optimize data lakes & data warehouses on S3, Redshift, AthenaDevelop Python-based ETL / ELT frameworks and reusable transformation modulesIntegrate data from RDBMS, APIs, Kafka / Kinesis, SaaS systems into unified datasetsLead data modeling, schema design, partitioning, and performance optimizationEnsure data quality, lineage, and observability using AWS Data Catalog, Glue Data Quality, or equivalent toolsDefine 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 workloadsImplement CI / CD pipelines for data workflows using AWS CodePipeline, GitHub Actions, or Cloud BuildProvide technical leadership, code reviews, and mentoring for junior engineersMonitor and optimize data infrastructure, troubleshoot failures, and lead capacity planningMandatory Skills
5–10 years of hands-on Data Engineering experienceStrong expertise in Python (pandas, PySpark, boto3, SQLAlchemy)Deep experience with AWS Data Services :AWS Glue, Lambda, EMR, Step FunctionsDynamoDB, Redshift, Athena, S3Kinesis, IAM, CloudWatchStrong SQL, data modeling, performance tuningExperience designing data lakes, data warehouses, streaming pipelinesHands-on ETL / ELT development, partitioning, data validationExperience with Git and CI / CD for data pipelinesKnowledge of containerization (Docker / Kubernetes) and DevOps basics