About the Role:

We are looking for a highly skilled and motivated Senior Data Engineer to lead the design and development of scalable, secure, and high-performance data pipelines and lakehouse architectures on AWS. You will play a critical role in building and optimizing our data infrastructure, enabling real-time and batch analytics across structured and semi-structured data sources.

Key Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue, Glue Studio, and Glue Workflows
Build and manage data lakes and lakehouses using S3, Lake Formation, and Glue Data Catalog
Enable interactive and federated querying using Athena, Redshift Spectrum, and Presto
Ingest and process streaming data using Amazon Kinesis (Data Streams, Firehose)
Integrate and transform data from SQL and NoSQL sources (e.g., RDS, DynamoDB, MongoDB)
Implement data governance, lineage, and access control using Lake Formation, IAM, and resource policies
Optimize performance, cost, scalability, and storage efficiency across pipelines, catalog layers, and compute frameworks
Implement data quality checks, validation frameworks, and observability mechanisms to ensure reliable, trustworthy datasets




Work with data scientists and analytics teams to deliver curated, clean, and production-ready datasets for ML, BI, and reporting
Ensure compliance with security, encryption, auditing, and regulatory standards
Develop architectural diagrams, data models, transformation logic, and operational documentation
Collaborate in Agile/Scrum processes involving sprint planning, estimation, and retrospectives
Troubleshoot production issues, perform root cause analysis, and drive continuous improvement of data systems

Required Skills & Qualifications:

Category

Requirements

ETL & Data Pipelines

Solid experience with AWS Glue, PySpark, Athena, and Glue Data Catalog

Data Storage

Proficient with Amazon S3, Redshift Spectrum, RDS, DynamoDB, and Lake Formation

Streaming

Hands-on with Amazon Kinesis (Data Streams, Firehose)

Data Modeling

Robust knowledge of:
SQL & NoSQL design
Partitioning strategies
Schema evolution and versioning
Performance tuning and query optimization
Data normalization vs. denormalization strategies

📌 Aws Data Engineer Bng/chn/hyd Permanent Role With Mnc Hyderabad
🏢 MNC Group
📍 Hyderabad