21 days ago
Hyderābād, IndiaMid Level
Responsibilities
- Build end-to-end ETL and event-streaming data pipelines from varied data sources and systems.
- Create datasets for analytics, reporting, and machine learning use cases.
- Evaluate and implement big-data technologies to optimize processing of extremely large datasets.
- Analyze business processes, logical data models, and relational database implementations.
- Write high-performing and optimized SQL queries.
- Execute research projects and generate practical results and recommendations.
- Design automated data processing solutions and data quality controls.
Requirements
- Bachelor’s degree.
- At least 3 years of data engineering experience.
- At least 3 years of SQL experience.
- Experience with data modeling, data warehousing, and ETL pipeline development.
- Experience with at least one modern scripting or programming language such as Python, Java, Scala, or NodeJS.
- Experience with big-data technologies such as Hadoop, Hive, Spark, or EMR.
- Experience with non-relational databases or data stores, including object storage, document or key-value stores, graph databases, or column-family databases.
- Preferred qualifications include a master’s degree in computer science, engineering, analytics, mathematics, statistics, or IT, or equivalent.
- Preferred qualifications include 5+ years of data engineering experience and experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
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.