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Job Description Position

AWS Lead Architect

AWS Practice Responsibilities

Consult, Design, build and operationalize large scale enterprise data solutions using one or more of AWS data and analytics services in combination with 3rd parties - Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue, Snowflake and Databricks.
Analyse, re-architect and re-platform on-premises data stores/ Databases to up-to-date data platforms on AWS cloud using AWS or 3rd party services.
Design and build production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, Scala.
Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, DynamoDB, RDS, S3
Design and implement data engineering, ingestion and curation functions on AWS cloud using AWS native or custom programming.




Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud as part of customer consultation and business proposals.
Participate in client design workshops and provide trade-offs and recommendations towards building solutions.
Mentor other engineers in coding best practices and problem solving

Requirements

11 - 16 years of experience in AWS
Experience and knowledge of Big Data Architectures, on cloud and on premise
Proficiency in AWS Collection Services: Kinesis, Kafka, Database Migration Service
Proficiency in AWS main Storage Service: S3, EBS, EFS
Proficiency in AWS main Compute Service: EC2, Lambda, ECS, EKS
Proven experience in: Java, Scala, Python, and shell scripting.
Working experience with: AWS Athena and Glue Pyspark, EMR, DynamoDB, Redshift, Kinesis, Lambda, Apache Spark, Databricks on AWS, Snowflake on AWS
Proficient in AWS Redshift, S3, Glue, Athena, DynamoDB
AWS Certification: AWS Certified Solutions Architect and/or AWS Certified Dat

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