Akkodis is seeking a
Lead AWS Platform/Data Engineering Lead
for a contract position with a client in Toronto, ON (Hybrid). Ideally looking for experience with
10–12 years in Big Data,
Python, SQL, Spark, and Terraform ,
designing and implementing data pipelines on AWS using native services &
configurable AWS services , Amazon Neptune DB,
5+ years in AWS (data-focused)
, Strong Experience with AWS Services: S3, Lake Formation, Glue, EMR, EC2 Athena, Lambda, EventBridge, SNS, SQS preference would be someone with the required skills and experience, particularly in large organizations.
Title: Lead AWS Platform/Data Engineering Lead
Location: Toronto ON(4 Days onsite)
Note:
Looking for at least 12+ years of experience; profiles with less than 12 years will be rejected by the client.
Call Notes from HM
• Strong expertise in
Python, SQL, Spark, Terraform and AWS Services: S3, Lake Formation, Glue, EMR, EC2 Athena, Lambda, EventBridge, SNS, SQS
• Hands-on experience in
designing and implementing data pipelines on AWS using native services &
configurable AWS services
• Experience with Amazon Neptune DB
• Proven experience
leading teams with strong communication skills
• 5+ years in AWS (data-focused)
and
10–12 years in Big Data
Must Have Technical/Functional Skills
Client is looking for engineers with the following skills:
• Strong Experience with AWS Services: S3, Lake Formation, Glue, EMR, EC2 Athena, Lambda, EventBridge, SNS, SQS
• Strong Experience in SQL, Python and Spark for Data Engineering tasks
• Expertise in Terraform
• Experience in designing and implementing Data Pipeline on AWS using native and configurable AWS services
• Excellent design and troubleshooting skills.
• Proficiency in Apache Spark for distributed data processing
• Experience with Amazon Neptune DB for graph-based metadata management
• Strong understanding of Data lake architecture, data governance and security best practices
• Strengthen Entitlement capability
• Launch self-serve data subscription and sharing of data products through Data Portal
• Improve data discovery by displaying composite data products only, simplifying catalog organization, Low Latency Solutions
• Build, design and implement scalable data lake architecture using AWS S3 and Lakeformation
• Build and optimize ETL Pipelines using AWS Glue, EMR and Spark
• Implement Event-Driven workflows using EventBridge, SNS and SQS
• Design and query datasets using Athena
• Manage metadata and data lineage using Amazon Neptune DB
• Expose APIs for data subscription and sharing using API Gateway and AWS Lambda
• Automate infrastructure provisioning using Terraform
• Ensure data security and compliance by implementing robust IAM policies and access controls.
• Develop and maintain a self-serve data portal using Angular and integrate it with backend service
Managerial Skills (Must Have)
• Strong Communication Skills
• Experience in Leading Teams
