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AWS Data Architect
Job in
Columbia, Lexington County, South Carolina, 29228, USA
Listed on 2026-02-28
Listing for:
Centraprise
Seasonal/Temporary
position Listed on 2026-02-28
Job specializations:
-
IT/Tech
Data Engineer, Cloud Computing, AWS, IT Consultant
Job Description & How to Apply Below
Overview
Columbia, SC (Initial 4-6 weeks Onsite then Remote)
12+ Months Contract
Job DescriptionWe 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.
CoreRoles & Responsibilities
- 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 Quick Sight.
- 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.
- 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 Cloud Formation.
- Performance: Tune Redshift (distribution styles/sort keys) and optimize SQL/Spark query performance for low-latency BI.
- Fin Ops: 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.
- 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 Systems: Deep expertise in MS SQL Server, SSIS, SSRS, Crystal Reports, Power BI, Tableau, and Hyperion.
- Languages: Advanced Python and SQL (T-SQL and Spark
SQL). - Dev Ops: Git-based CI/CD pipelines (Jenkins, Git Lab, or AWS Code Pipeline).
Data Formats: Deep understanding of Parquet, Avro, and Delta Lake.
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