AWS Data Engineer (8-12 yrs)

Role AWS Data Engineer.

Location : Gurugram, India (Hybrid).

Type : Permanent.

Job Description :

Key Responsibilities :

- Data Pipeline Development : Design, develop, and optimize end-to-end data pipelines for extracting, transforming, and loading (ETL) large volumes of data from diverse sources into data warehouses or lakes.

- Cloud Infrastructure Management : Implement and manage data processing and storage solutions in AWS (Amazon Web Services) using services like S3, Redshift, Lambda, Glue, Kinesis, and others.

- Data Modeling : Collaborate with data scientists, analysts, and business stakeholders to define data requirements and design optimal data models for reporting and analysis.

- Performance Tuning & Optimization : Identify bottlenecks and optimize query performance, pipeline processes, and cloud resources to ensure cost-effective and scalable data workflows.

- Automation & Scripting : Develop automated data workflows and scripts to improve operational efficiency using Python, SQL, or other scripting languages.

- Collaboration & Documentation : Work closely with data analysts, data scientists, and other engineering teams to ensure data availability, integrity, and quality. Document processes, architectures, and solutions clearly.

- Data Quality & Governance : Ensure the accuracy, consistency, and completeness of data. Implement and maintain data governance policies to ensure compliance and security standards are met.

- Troubleshooting & Support : Provide ongoing support for data pipelines and troubleshoot issues related to data integration, performance, and system reliability.

Qualifications :

Essential Skills :

- Experience : 8+ years of professional experience as a Data Engineer, with a strong background in building and optimizing data pipelines and working with large-scale datasets.

- AWS Experience : Hands-on experience with AWS cloud services, particularly S3, Lambda, Glue, Redshift, RDS, and EC2.

- ETL Processes.

- Programming Languages : Proficiency in Python, SQL, and other scripting languages (i.e., Bash, Scala, Java).

- Data Warehousing.

- Data Modeling.

- Version Control & CI/CD.

Desirable Skills :

- Big Data Technologies.

- Containerization & Orchestration.

- Data Security.

- Data Streaming.

- Business Intelligence Tools.

- Agile Methodology.