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- Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience
- Experience implementing, supporting data lakes, data warehouses and data applications on AWS for large enterprises
- Solid experience of AWS services such as CloudFormation, S3, Athena , Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
- Solid experience implementing solutions on AWS based data lakes.
- Experience in AWS data lake/data warehouse/business analytics
- Experience in system analysis, design, development, and implementation of data ingestion pipeline in AWS
- Knowledge of ETL/ELT
- End-to-end data solutions (ingest, storage, integration, processing, access) on AWS
- Architect and implement CI/CD strategy for EDP
- Implement high velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred)
- Migrate data from traditional relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift
- Migrate data from APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift
- Implement POCs on any new technology or tools to be implemented on EDP and onboard for real use-case
- AWS Solutions Architect or AWS Developer Certification preferred Requirements :
- 5+ years of experience as Data engineer
- Experience developing business applications using SQL databases.
- Experience working Cloud (AWS preferred)
- Should have good experience with AWS Services – S3, Athena, Glue, Lambda, Step Functions, SQS, Redshift.
- 3+ Years of experience with Spark / Scala.
- Designing, building and maintaining efficient, reusable, and reliable architecture and code.
- Build reliable and robust Data ingestion pipelines (within AWS, onprem to AWS ,etc)
- Ensure the best possible performance and quality of high scale data engineering project
- Participate in the architecture and system design discussions
- Independently perform hands on development and unit testing of the applications;
- Collaborate with the development team and build individual components into complex enterprise web systems;
- Work in a team environment with product, production operation, QE/QA and cross functional teams to deliver a project throughout the whole software development cycle;
- Responsible to identify and resolve any performance issues
- Keep up to date with new technology development and implementation
- Participate in code review to make sure standards and best practices are met
AWS Data Engineer with Spark/Scala Background - Newark, United States - PamTen
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