Senior Database Engineer – Distributed Data Systems, Automation & Cloud Modernization

CGI•Westlake, TX

3d•Hybrid

About The Position

CGI is seeking to hire a Sr. Database Engineer experienced in Modernizing enterprise scale data platforms that support millions of customers. This role requires engineers who understand not just SQL, but the full lifecycle of distributed data systems, automation, performance tuning, and cloud native transformation. As a Senior Database Engineer, you’ll design, optimize, and modernize the mission‑critical data backbone powering large‑scale record‑keeping and representative‑facing applications. Your work across database engineering, ETL pipelines, scripting, automation frameworks, and cloud‑ready architectures will directly influence system performance, data quality, platform reliability, and the organization’s ability to modernize at scale—supporting essential financial and protection services relied on every day. This is a hands‑on, highly technical role where your expertise shapes the future of enterprise data platforms and delivers measurable, real‑world impact. This role is based in Westlake, TX in a hybrid working model.

Requirements

6+ years of hands-on database engineering experience in enterprise environments
Deep proficiency in Oracle SQL, PL/SQL, query optimization, and performance tuning
Strong scripting experience (Shell, Python, or similar) with a focus on automation
Experience with Informatica or other ETL/ELT platforms
Exposure to cloud platforms (AWS, Azure) and cloud ready data architectures
Understanding of distributed systems, data modeling, and high availability patterns
Experience supporting large scale, high volume transactional systems
Strong debugging, triage, and problem-solving skills across complex environments

Responsibilities

Design, develop, and optimize complex SQL queries, PL/SQL packages, stored procedures, triggers, and functions
Perform deep dive performance tuning using execution plans, indexing strategies, partitioning, and advanced Oracle features
Analyze query patterns, data access paths, and workload characteristics to improve throughput and latency
Implement data integrity, referential constraints, and schema evolution strategies for high volume systems
Build automation frameworks using Shell, Python, or similar scripting languages
Automate database deployments, schema migrations, data refreshes, and validation workflows
Develop internal tools to streamline developer productivity, reduce manual operations, and improve reliability
Integrate automation into CI/CD pipelines for database centric components
Design and maintain ETL workflows using Informatica or comparable tools
Optimize data ingestion, transformation, and distribution across upstream and downstream systems
Implement data quality checks, reconciliation logic, and error handling frameworks
Support batch, near real time, and event driven data movement patterns
Contribute to cloud migration strategies across AWS, or Azure
Support modernization of legacy data flows into cloud native equivalents
Work with cloud storage, managed databases, and serverless compute patterns
Apply cloud security, IAM, encryption, and compliance best practices
Diagnose and resolve complex issues across production and non-production environments
Perform root cause analysis on performance bottlenecks, data inconsistencies, and integration failures
Enhance observability through logs, metrics, alerts, and dashboards
Participate in on call rotations and incident response processes