AWS Data Architect

Job Description

TCS HIRING!! ROLE: AWS Data Architect YEAR OF EXP: 8 + YEARS LOCATION: Chennai/ Pune / Bangalore / Hyd Data Architect: Must have: Relational SQL/ Caching expertise – Deep knowledge of Amazon Aurora PostgreSQL, ElastiCache etc.. Data modeling – Experience in OLTP and OLAP schemas, normalization, denormalization, indexing, and partitioning. Schema design & migration – Defining best practices for schema evolution when migrating from SQL Server to PostgreSQL. Data governance – Designing data lifecycle policies, archival strategies, and regulatory compliance frameworks. AWS Glue & AWS DMS – Leading data migration strategies to Aurora PostgreSQL. ETL & Data Pipelines – Expertise in Extract, Transform, Load (ETL) workflows . Glue jobs features and event-driven architectures. Data transformation & mapping – PostgreSQL PL/pgSQL migration / transformation expertise while ensuring data integrity. Cross-platform data integration – Connecting cloud and on-premises / other cloud data sources. AWS Data Services – Strong experience in S3, Glue, Lambda, Redshift, Athena, and Kinesis. Infrastructure as Code (IaC) – Using Terraform, CloudFormation, or AWS CDK for database provisioning. Security & Compliance – Implementing IAM, encryption (AWS KMS), access control policies, and compliance frameworks (eg. GDPR ,PII). Query tuning & indexing strategies – Optimizing queries for high performance. Capacity planning & scaling – Ensuring high availability, failover mechanisms, and auto-scaling strategies. Data partitioning & storage optimization – Designing cost-efficient hot/cold data storage policies. Should have experience with setting up the AWS architecture as per the project requirements Good to have: Data Warehousing – Expertise in Amazon Redshift, Snowflake, or BigQuery. Big Data Processing – Familiarity with Apache Spark, EMR, Hadoop, or Kinesis. Data Lakes & Analytics – Experience in AWS Lake Formation, Glue Catalog, and Athena. Machine Learning Pipelines – Understanding of SageMaker, BedRock etc. for AI-driven analytics. CI/CD for Data Pipelines – Knowledge of AWS CodePipeline, Jenkins, or GitHub Actions. Serverless Data Architectures – Experience with event-driven systems (SNS, SQS, Step Functions). Show more Show less