Key Responsibilities:

Design and implement scalable, high-performance data pipelines using AWS services
Develop and optimize ETL processes using AWS Glue, EMR, and Lambda
Build and maintain data lakes using S3 and Delta Lake
Create and manage analytics solutions using Amazon Athena and Redshift
Design and implement database solutions using Aurora, RDS, and DynamoDB
Develop serverless workflows using AWS Step Functions
Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL
Ensure data quality, security, and compliance with industry standards
Collaborate with data scientists and analysts to support their data needs
Optimize data architecture for performance and cost-efficiency
Troubleshoot and resolve data pipeline and infrastructure issues

Required Qualifications:

bachelor's degree in computer science, Information Technology, or related field
Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS
Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S3
Experience with data lake technologies, particularly Delta Lake
Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL
Proficiency in Python and PySpark programming
Strong SQL skills and experience with PostgreSQL
Experience with AWS Step Functions for workflow orchestration

Technical Skills:

AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB, Step Functions
Big Data: Hadoop, Spark, Delta Lake
Programming: Python, PySpark
Databases: SQL, PostgreSQL, NoSQL
Data Warehousing and Analytics
ETL/ELT processes
Data Lake architectures
Version control: Git
Agile methodologies

Data Engineer Senior Consultant

T&T- EAD- Engg- AWS Data Engineer- Senior Consultant/Consultant