Bachelor's degree in computer science, Information Systems, or a related field. • Python Programming: Strong proficiency in Python for data manipulation, scripting, and ETL tasks. • AWS Services: Experience with AWS services such as Glue, Lambda, S3, Redshift, and EMR. • Big Data Technologies: Familiarity with big data technologies like Hadoop, Hive, and Spark. • Data Modeling: Knowledge of data modeling concepts and best practices. • SQL and NoSQL Databases: Proficiency in SQL and understanding of NoSQL databases. • Data Governance and Security: Understanding of data governance principles and security practices.
Roles & Responsibilities :
Designing and Building Data Pipelines: Create efficient and scalable data pipelines using AWS services such as AWS Glue, Lambda, Step Functions, and S3. • Data Ingestion and Transformation: Extract, transform, and load (ETL) data from various sources into AWS data lakes or data warehouses. • Data Modeling and Warehousing: Design and implement data models for efficient querying and reporting. • Data Governance and Security: Ensure data quality, governance, and security best practices. • Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.