Engineering Manager - Data Management

Job title: Engineering Manager - Data Management

About the Role Engineering Manager – Data Management leads teams responsible for delivering platform changes, upgrades, and continuous improvements across enterprise data management products and customer environments. This role ensures changes are delivered safely, predictably, and in compliance, while scaling engineering excellence through strong people leadership, governance, and adoption of data-driven and AI-enabled practices. The Engineering Manager acts as a bridge between technical execution, change governance, and customer impact, ensuring long-term platform stability and evolution.

What You'll Do

• End-to-end delivery of data management changes, upgrades, and major releases across environments. Ensure all changes follow approved change management, validation, and rollback frameworks. Accountable for release readiness, production stability, and post-release outcomes.
• Provide technical leadership across data ingestion, transformation, validation, reconciliation, and storage layers. Ensure data quality, integrity, and consistency are preserved during upgrades and migrations. Guide architectural decisions to balance scalability, performance, and operational stability.
• Identify and mitigate technical, operational, and data risks; ensure compliance with data governance, audit, and regulatory expectations, including segregation of environments. Maintain strong documentation and audit readiness for all changes.
• Lead and develop engineering, QA, and release/change professionals. Drive performance management, career growth, mentoring, and succession planning. Foster a culture of accountability, quality, continuous improvement, and psychological safety.
• Partner with product, operations, compliance, and customer-facing teams to align priorities. Communicate change scope, risks, timelines, and outcomes clearly to stakeholders. Support escalations with data-driven analysis, corrective actions, and preventive improvements.
• Continuously improve change, release, and validation processes to reduce defects and recovery time. Promote standardization, automation, and repeatability in upgrade execution. Track delivery and operational metrics to improve predictability and quality.

What We're Looking For

• Proven experience managing engineering teams in complex, data-centric environments; strong understanding of data platforms, releases, and change governance.
• Demonstrated ability to balance technical depth, people leadership, and stakeholder management. Experience applying automation and AI-assisted practices in engineering or operations is a strong advantage.
• 14–15 years of software engineering experience with significant time in .NET/C# ecosystems; 5+ years leading engineers; experience working in large, distributed, international organizations.
• Technical Experience: .NET/C# Core; strong fundamentals of WPF, WCF, WWF; async programming, concurrency, performance; Web API, .NET Core, microservices; Docker and container-based apps; Azure DevOps Pipelines; code reviews and engineering standards; performance optimization; multi-threaded, performance-intensive systems; Git/TFS and CI/CD.
• AI Elements: A mindset and practical application for AI-assisted engineering productivity, developer experience, quality, risk, and reliability; building AI-assisted coding practices and defining done criteria; using AI for test prioritization and anomaly detection.

Compensation & Benefits

• Not specified