Job type
- Full-time
- Quick Apply
Job description
Key Responsibilities
- Database Modernization & Migration: Lead heterogeneous data migrations from legacy enterprise databases to AWS-managed targets using AWS Schema Conversion Tool (SCT) and AWS Database Migration Service (DMS).
- PostgreSQL Architecture: Design, implement, and manage highly scalable Postgres Architecture in AWS, focusing heavily on modern serverless deployment options (such as Amazon Aurora PostgreSQL Serverless v2).
- DBA & Performance Tuning: Execute core database administration duties, query optimization, indexing strategies, connection pooling configurations (e.g., PgBouncer), and latency reduction for high-volume transactions.
- ETL & Data Pipeline Design: Build, scale, and maintain efficient ETL workflows structured around medallion architecture (Bronze, Silver, and Gold tiers) for streamlined analytics and reporting.
- Infrastructure as Code (IaC): Write and maintain Terraform configurations to automate the provisioning, scaling, and management of AWS cloud and database resources.
Required Skills & Qualifications
- Deep practical experience with AWS SCT and AWS DMS for handling schema translations, data mapping, initial full-loads, and ongoing CDC (Change Data Capture) replication.
- PostgreSQL DBA Expertise: Comprehensive database administration skills on PostgreSQL, specializing in performance tuning, resource monitoring, and deadlock/lock conflict troubleshooting.
- AWS & Serverless Expertise: Strong architectural background in AWS cloud services, specifically relational database design and serverless configurations.
- Heterogeneous Migration Experience: Proven track record of executing complex data migrations across different legacy database platforms onto cloud-native PostgreSQL.
- Data Engineering & ETL: Solid foundational knowledge of ETL concepts combined with practical experience implementing medallion architecture for modern data lakes and warehouses.
- Automation: Hands-on proficiency with Terraform to manage AWS resources securely and repeatably