Data Engineer I, Amazon
Teknik, data och digitalt · Data, AI och analys · Data engineering
I korthet
Amazon seeks a Data Engineer I in Karnataka to build and manage data engineering solutions impacting global revenue. You will design and implement scalable ETL processes, work with large datasets, and deliver data as a service to support business decision-making.
Ansvarsområden
- Design, implement, and support a platform providing ad-hoc access to large data sets.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
- Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, Redshift, and OLAP technologies.
- Model data and metadata for ad-hoc and pre-built reporting.
- Interface with business customers, gathering requirements and delivering complete reporting solutions.
- Build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
- Build and deliver high quality data sets to support business analyst, data scientists, and customer reporting needs.
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
Krav
- 2+ years of data engineering experience.
- Experience with SQL.
- Experience with one or more scripting language (e.g., Python, KornShell).
- Experience with data modeling, warehousing and building ETL pipelines.
Önskade kvalifikationer
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR.
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
- Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments.
Förmåner
- Inclusive culture.
- Empowerment to deliver best results.
- Workplace accommodations for individuals with disabilities.
#Data Engineering#ETL#Data Modeling#SQL#Python#Spark#Big Data#AWS#Redshift#Amazon