Senior AWS Data Architect (onsite)

Job Description: Senior AWS Data Architect
Role Overview
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
1. 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.
2. 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.

3. 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.
Data Stores: DynamoDB, Aurora (PostgreSQL/MySQL), Neptune.
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.