Associate Staff Database Engineer [T500-27352]

Talent500 is hiring for one of its clients.

Who are we: Core Insurance Platforms (CIP) is Zurich’s global capability responsible for building, running, and evolving core insurance technology. We set a unified, scalable operating model—covering governance, standards, architecture, service delivery, and reuse—so our business units can deliver at speed and scale. CIP is the strategic steward of Zurich’s Guidewire ecosystem, aligning platform roadmaps to business strategy while driving stability, modernization, reduced supplier dependency, and long term cost efficiency. India delivery center is one of our global delivery and capability hub. We bring together experts in AI, engineering, analysis, quality, and architecture to deliver product & process solutions, application run services, change and transformation initiatives, and centralized platform services across both on prem and Guidewire Cloud environments. Our teams operate from multiple global delivery centers, supporting Zurich’s business units worldwide.

Role Summary: Senior Database Engineer with 10+ years of hands-on experience designing, optimizing, securing, and operating enterprise database platforms, with supporting expertise in DevOps practices and automation. The Senior Database engineer role helps design, troubleshoot. This role operates in an AI-first database and platform engineering environment, where data platform design, performance tuning, resilience, automation, and delivery processes are enhanced through AI-assisted insights to improve availability, scalability, security, and engineering efficiency across cloud and containerized ecosystems.

• Experience Level: 10+ years in database engineering, platform operations, and DevOps environments
• Role Type: Full-time, enterprise platform engineering role
• Work Model: Hybrid / Cloud-first / Global team collaboration
• Primary Function: Responsible for the design, implementation, optimization, and reliability of enterprise database platforms within an AI-first DevOps ecosystem.
• Technology Landscape:
• Databases: MS SQL Server, Oracle, Aurora PostgreSQL
• Cloud Platforms: AWS, Azure
• Container Platforms: AKS, EKS
• IaC & Automation: Terraform, PowerShell, Python, YAML
• CI/CD & Tools: Azure DevOps, Jenkins, Git, JIRA
• Monitoring: Dynatrace, Datadog
• Security: HashiCorp Vault, access controls, encryption tools
• Operating Systems: Windows, Linux

Success Profile:

• Strong ownership mindset with end-to-end accountability for database platforms
• Deep technical expertise with practical DevOps implementation experience
• Ability to translate business and application needs into scalable data platform designs
• Proactive approach to automation, resilience, and continuous improvement
• Strong collaboration and communication skills in global, cross-functional teams

Must Have:

• Strong experience with enterprise database platforms (MS SQL, Oracle, Aurora PostgreSQL, etc.) including architecture, planning, sizing, performance tuning, troubleshooting, resilience, and implementation.
• Experience with ETL, data movement, and integration processes, with a strong understanding of how pipelines impact database performance, reliability, and downstream consumption.
• Experience automating database infrastructure and platform provisioning with Infrastructure as Code using Terraform, leveraging AI-assisted validation and optimization to improve consistency, reduce drift, and accelerate delivery
• Experience with managed Kubernetes services such as AKS and EKS, including supporting platform workloads in containerized environments and working with engineering teams on deployment and operational processes
• Experience with PowerShell, Python, and YAML, leveraging AI-driven automation to enhance development and operations.
• Experience with public cloud database and infrastructure services in AWS and Azure, leveraging AI-driven insights to optimize performance, cost, backup strategy, and scalability
• Experience securing database platforms and application integrations with secrets managers such as HashiCorp Vault, leveraging AI-assisted analysis to strengthen governance, access controls, and security posture
• Hands-on experience with CI/CD and release processes using Azure DevOps, Jenkins, Git, JIRA, and related tools to support database change management, automation, and reliable production deployments
• Experience maintaining AWS and Azure infrastructure that supports database services, including networking, access, certificates, and load balancing, using AI-assisted monitoring and analysis to improve reliability and reduce misconfigurations
• Experience with monitoring and observability tools such as Dynatrace or Datadog, leveraging AI-based anomaly detection and telemetry insights to proactively identify database and platform issues
• Experience with Windows and Linux operating systems that underpin database platforms, leveraging AI-assisted troubleshooting to accelerate root cause analysis and system optimization
• Solid understanding of network, storage, and DNS troubleshooting as it relates to database connectivity, replication, failover, and application integration
• Demonstrated ability to apply AI-assisted techniques to improve database automation, platform standardization, and deployment workflows in enterprise environments
• Experience using AI-assisted monitoring, anomaly detection, and trend analysis to identify recurring incident, performance, and capacity patterns across database and platform environments
• Track record of delivering measurable improvements in database performance, uptime, recovery posture, and operational efficiency through automation and engineering best practices
• Demonstrated ability to establish and promote AI-first database engineering practices with supporting DevOps discipline in secure, regulated, or large-scale enterprise environments
• Ensure responsible use of AI aligned with security, data privacy, regulatory compliance, and enterprise data management requirements

Database Platform Engineering & Operations:

• Design, deploy, and manage enterprise database platforms (MS SQL, Oracle, Aurora PostgreSQL) across hybrid and cloud environments.
• Ensure high availability, scalability, and resiliency through optimized architecture, replication, failover, and backup strategies.
• Continuously improve platform reliability and uptime using automation, monitoring insights, and engineering best practices.

Performance Optimization & Troubleshooting:

• Monitor, analyze, and tune database performance across environments using observability tools (Dynatrace, Datadog).
• Lead root cause analysis for database and platform incidents, leveraging AI-assisted diagnostics to accelerate resolution.
• Optimize queries, indexing, storage, and workloads to improve performance and reduce infrastructure costs.

DevOps & Automation Enablement:

• Automate database provisioning, configuration, and lifecycle management using Infrastructure as Code (Terraform).
• Support CI/CD pipelines for database deployments and schema changes using Azure DevOps, Jenkins, and Git.
• Build standardized, reusable automation frameworks leveraging Python, PowerShell, YAML, and AI-assisted scripting.

Cloud & Container Integration:

• Design and support database services in AWS and Azure, optimizing for cost, performance, and scalability.
• Collaborate with platform teams to deploy and operate containerized workloads on AKS/EKS.
• Ensure seamless integration between database services and microservices architectures.

Data Integration & Pipeline Support:

• Support ETL processes, data ingestion pipelines, and downstream data consumers.
• Ensure pipeline performance does not negatively impact database stability or availability.
• Optimize data flows and integration patterns for reliability and scalability.

Security & Compliance:

• Implement database security best practices including encryption, access control, auditing, and secrets management (e.g., HashiCorp Vault).
• Ensure compliance with enterprise security, data privacy, and regulatory standards.
• Apply AI-assisted security insights to identify vulnerabilities and strengthen controls.

Monitoring, Observability & Incident Management:

• Define and implement monitoring strategy for databases and supporting infrastructure.
• Use AI-driven anomaly detection and trend analysis to proactively identify risks.
• Participate in incident response, escalation, and problem management processes.

Infrastructure & Platform Support:

• Manage underlying infrastructure components including networking, certificates, load balancing, storage, and DNS.
• Support both Windows and Linux environments underpinning database platforms.
• Ensure platform consistency, reduce configuration drift, and improve operational stability.

AI-First Engineering Practices:

• Leverage AI-assisted tools for performance optimization, anomaly detection, log analysis, and troubleshooting.
• Continuously identify opportunities to improve automation, standardization, and engineering efficiency using AI.
• Establish best practices for responsible and secure use of AI in database engineering.

Collaboration & Governance:

• Work closely with application teams, DevOps engineers, and architecture teams to align on database design and integration.
• Support change management, release governance, and audit readiness.
• Contribute to platform standards, documentation, and continuous improvement initiatives.