AWS Data Engineer - ETL

Role AWS Data : 4-10 : Bangalore ( Hybrid -3 Days : Immediate joiner 7 Days : - Data Pipeline Development : Design and implement data pipelines using a variety of AWS services, including : - Amazon S3 : For data storage and management. - AWS Glue : For ETL (Extract, Transform, Load) processes, data cataloging, and data integration. - Apache Spark (PySpark) on Amazon EMR : For large-scale data processing and transformation. - Data Processing and Transformation : Develop and maintain data processing and transformation scripts using Python and SQL to extract, clean, transform, and load data from various sources. - AWS Database Services : Optimize data storage and retrieval using AWS database services, such as : - Amazon RDS : For relational database solutions. - Amazon Redshift : For data warehousing and analytics. - Amazon DynamoDB : For NoSQL database solutions. - Data Warehousing : Build different types of data warehousing layers (e.g., staging, data warehouse, data marts) based on specific use cases and business requirements. - ETL and Data Modeling : Utilize expertise in SQL and possess a strong understanding of ETL processes, data modeling techniques (e.g., dimensional modeling), and data warehousing concepts. - Data Quality and Availability : Ensure the accuracy, consistency, and availability of data to internal and external customers. Understand how technical decisions can impact business analytics and reporting. - AWS Services Expertise : Demonstrate proficiency and hands-on experience with the following AWS services : - Amazon S3 : Data storage and management. - AWS Glue Studio : Visual ETL development and data integration. - Amazon Redshift : Data warehousing and analytics. - Amazon Athena : Interactive query service. - AWS Lambda : Serverless compute for data processing. - Amazon SQS : Message queuing for decoupled data : - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 4-10 years of experience in data engineering, with a strong focus on Skills : - Extensive hands-on experience with AWS data services (S3, Glue, EMR, RDS, Redshift, DynamoDB, Athena, Lambda, SQS). - Strong proficiency in Python and SQL. - Solid understanding of ETL processes, data modeling, and data warehousing concepts. - Experience in designing, building, and maintaining data pipelines. - Ability to optimize data storage and retrieval for performance and scalability. - Excellent problem-solving, analytical, and debugging skills. - Strong communication (written and verbal) and collaboration Skills : - AWS Certifications (AWS Certified Data Engineer Associate). - Experience with other data warehousing technologies. - Familiarity with big data technologies (Hadoop, Spark). - Experience with data visualization tools (Tableau, Power BI). - Knowledge of data governance and data quality principles. - Familiarity with the Pharma domain. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 5/1/2025