AWS Cloud Data Scientist
1 month ago
Pioneers in harnessing the power of Artificial Intelligence (AI) to deliver actionable insights and drive transformative change for businesses worldwide, E-Merge’s vision is to provide next-generation actionable insights to every company, globally, by harnessing the value of data using high-performance, interoperable, and simplified solutions. They are currently looking for an AWS Data Engineer to join their fast-paced and dynamic team.
Responsibilities
- Design, build, and operationalize large-scale enterprise data solutions and applications
- Analyze, re-architect, and re-platform on-premise data warehouses to data platforms on AWS cloud using AWS or 3rd party services and Kafka
- Design and build production data pipelines from ingestion to consumption within a big data architecture, using Java, PySpark, Scala, Kafka
- Design and implement data engineering, ingestion, and curation functions on AWS cloud using AWS native or custom programming
- Perform detailed assessments of current-state data platforms and create an appropriate transition path to AWS cloud
- Design, implement, and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, AWS big data technologies, and Kafka
- Create and support real-time data pipelines built on AWS technologies including Glue, Lambda, Step Functions, PySpark, Athena, and Kafka
- Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency
Qualifications and Experience:
- Bachelor’s Degree in Computer Science, Information Technology, or other relevant fields
- 5-8 years of experience
- Has experience in any of the following: AWS Athena and Glue, PySpark, DynamoDB, Redshift, Lambda, Step Functions, and Kafka
- Proficient in AWS Redshift, S3, Glue, Athena, PySpark, Step Functions, Glue Workflows, Kafka, and Delta.io
- Knowledge of software engineering best practices across the development lifecycle
- Experience with big data tools is a must: Delta.io, PySpark, Kafka, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
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