Aws Data Architect, Columbia

Overview
Columbia, SC (Initial 4-6 weeks Onsite then Remote)
12+ Months Contract
Job Description
We are seeking a highly experienced, hands-on AWS Data Architect to lead the design and execution of our cloud data ecosystem.
The primary focus is the end-to-end migration and modernization of legacy on-premise Microsoft stacks (SQL Server EDW, SSIS, and multi-platform reporting) to a cloud-native AWS architecture.
Core Roles & Responsibilities
Architectural Strategy & Migration Design
Modern Data Architecture:
Design and evolve a Lakehouse/Mesh architecture using AWS S3, Glue, and Amazon Redshift.
Legacy EDW Migration:
Execute the migration strategy for moving MS SQL Server EDW to AWS, ensuring high performance and data integrity.
Pipeline Modernization:
Refactor legacy SSIS packages into cloud-native services using AWS Glue, Step Functions, or MWAA (Airflow).
BI & Report Modernization:
Lead the migration path for SSRS, Crystal Reports, Power BI, Tableau, and Hyperion to AWS-integrated environments or Amazon QuickSight.
Governance & Compute:
Implement multi-region scalability and robust governance using AWS Lake Formation and Glue Data Catalog, while optimizing compute via Serverless (Athena/Lambda) vs. Managed (EMR/MSK) strategies.
Hands-on Engineering & Implementation
ETL/ELT Conversion:
A development-heavy role refactoring SSIS logic into Python/Spark within AWS Glue or EMR.
Database Migration:
Hands-on use of AWS DMS and SCT to migrate data from MS SQL to RDS, Aurora, or Redshift.
Real-time Streaming:
Implement streaming solutions using Amazon Kinesis or Managed Kafka (MSK).
Infrastructure as Code (IaC):
Automate all deployments using Terraform, AWS CDK, or CloudFormation.
Optimization, Security & Compliance
Performance:
Tune Redshift (distribution styles/sort keys) and optimize SQL/Spark query performance for low-latency BI.
FinOps:
Monitor and reduce AWS spend via S3 lifecycle policies and Glue job optimization.
Security:
Design fine-grained access via IAM and Lake Formation; manage encryption using KMS and Secrets Manager.
Technical Skills & Experience Requirements
Mandatory AWS Expertise
Migration/Storage:
AWS DMS, SCT, Amazon S3 (Optimization & Replication).
Processing & Analytics:
AWS Glue, EMR, Lambda, Amazon Redshift (RA3), Amazon Athena.
Messaging & Orchestration:
Kinesis, MSK, SQS, Step Functions, MWAA (Airflow).
Legacy Stack & General Skills
Legacy Systems:
Deep expertise in MS SQL Server, SSIS, SSRS, Crystal Reports, Power BI, Tableau, and Hyperion.
Languages:
Advanced Python and SQL (T-SQL and SparkSQL).
DevOps:
Git-based CI/CD pipelines (Jenkins, GitLab, or AWS CodePipeline).
Data Formats:
Deep understanding of Parquet, Avro, and Delta Lake.
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