S

SimCorp

Provides integrated investment management software

Engineering Manager – Data Management

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNoida, Uttar Pradesh, IndiaNo salary listed

About the Job

Requirements

  • 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.
  • 14–15 years of overall software engineering experience, with significant time in .NET/C# ecosystems.
  • At least 5 years leading engineers through direct people leadership, owning delivery and engineering standards.
  • Proven ability to work effectively in large, distributed, international organizations and across levels.
  • Strong C# fundamentals and deep experience with Microsoft .NET Framework, including WPF, WCF, and WWF.
  • Strong understanding of asynchronous programming, concurrency, and performance considerations.
  • Strong experience with Web API, .NET Core, modern architecture patterns, microservices, and Docker/container-based applications.
  • Hands-on experience designing and operating Azure DevOps CI/CD pipelines, including quality gates and release orchestration.
  • Demonstrated ability to drive high-quality, efficient code reviews, enforce standards, and mentor engineers.
  • Proven track record in profiling and code optimization strategies.
  • Experience building and operating multithreaded, performance-intensive applications, with a strong understanding of concurrency patterns and pitfalls.
  • Strong experience with Git/TFS, branching, pull request workflows, and continuous builds integrated into CI/CD.
  • Ability to lead responsible adoption of AI-assisted practices in day-to-day engineering.
  • Ability to establish team practices for AI-assisted coding, including suggestions, refactoring support, and unit-test generation assistance, with clear review accountability and secure usage patterns.
  • Ability to build definition-of-done expectations for AI-assisted output, including tests, security checks, performance-impact review, and documentation.
  • Ability to use AI-assisted approaches to improve test prioritization and regression optimization, anomaly detection in logs/telemetry, root-cause analysis during incidents, and knowledge search across engineering artifacts.
  • Application must be submitted in English through the career site.

Responsibilities

  • Own 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.
  • Be 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 associated with changes and upgrades.
  • Ensure compliance with data governance, audit, and regulatory expectations, including segregation of environments.
  • Maintain documentation, traceability, and audit readiness for all changes.
  • Lead and develop engineering, quality assurance, 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 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.
  • Establish team practices for AI-assisted coding and secure usage, with accountable review of outputs.
  • Define completion expectations for AI-assisted outputs, including tests, security checks, performance-impact review, and documentation.
  • Use AI-assisted approaches to improve test prioritization and regression optimization, anomaly detection in logs/telemetry, root-cause analysis during incidents, and knowledge search across engineering artifacts.

Desired Qualifications

  • Experience applying automation and AI-assisted practices in engineering or operations is a strong advantage.
  • Experience in capital markets is a plus, preferably with buy-side firms such as asset managers, pension funds, and investment managers, and understanding of data workflows typical in investment operations and analytics.

About the Company

SimCorp

Provides integrated investment management software

SimCorp provides integrated software for the financial industry, offering a comprehensive suite of investment management solutions that support processes such as portfolio management, risk management, and accounting. Its products help large financial institutions streamline operations, control risks, and improve investment performance by delivering an end-to-end platform that covers front-, middle-, and back-office functions. The company differentiates itself through its scale and reach after being acquired by Deutsche Börse Group in 2024 and through the merger with Axioma, which added risk management and portfolio optimization capabilities to its offering. SimCorp’s goal is to provide a unified, reliable platform that helps clients manage investments efficiently while maintaining strong service and support.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Copenhagen, Denmark
Founded
1971

Recently Posted Jobs

Explore more opportunities at SimCorp

See more jobs