2 months ago
Bengaluru, IndiaMid Level
Responsibilities
- Design, implement, and support analytical data infrastructure for business intelligence and machine learning applications.
- Manage AWS resources including EC2, Redshift, and EMR-Spark.
- Build and maintain data pipelines supporting machine learning model development and training.
- Extract, transform, and load data from diverse sources using SQL and AWS big-data technologies.
- Collaborate with scientists, product managers, analysts, and technology teams on reporting, analysis, data integrity, validation, and documentation.
- Implement advanced analytics capabilities for statistical analysis, prediction, clustering, and machine learning.
- Automate and simplify reporting, analysis, and self-service customer support processes.
Requirements
- At least 3 years of data engineering experience.
- Experience with data modeling, data warehousing, and ETL pipeline development.
- Experience with SQL.
- Preferred experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Kinesis Data Firehose, Lambda, and IAM roles and permissions.
- Preferred experience with non-relational databases or data stores, including object storage, document or key-value stores, graph databases, and column-family databases.
Benefits
- Fixed-term contract role.
- Inclusive workplace culture with workplace accommodation or adjustment support during the application, hiring, interview, and onboarding processes.
Tech Stack
Categories
Data Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.