Delivery Manager-Investment Data Operations

Job purpose

The Investment Data Operations Transformation Lead / Project Manager will be responsible for leading investment-data operations, data transformation initiatives, and delivery workstreams across the organization.

The role requires a strong blend of investment-domain expertise, data management, technical proficiency, project leadership, and stakeholder engagement.

This is a hands-on techno-functional leadership role responsible for supervising business analysts and data operations teams while actively reviewing, validating, and challenging investment-data outputs. The incumbent will drive investment-data quality, reconciliation, migration, remediation, and governance activities while acting as the bridge between investment teams, operations stakeholders, technology teams, fund administrators, and external service providers.

The role will also lead strategic data-transformation initiatives, including the implementation and ongoing management of investment-data platforms, golden-record frameworks, automation solutions, and the Citco

Document Service continuous ingestion pipeline utilizing Azure Cloud technologies, Snowflake, SharePoint, and related data services.

Key responsibilities

Lead and supervise a team of Business Analysts and Data Operations professionals, ensuring quality, accuracy, and timely delivery of investment-data initiatives.

Manage project plans, priorities, resources, risks, dependencies, issues, and stakeholder communications across multiple workstreams.

Oversee investment-data collection, enrichment, cleansing, remediation, and maintenance from internal and external data sources.

Lead reconciliation of investment records across fund administrators, CRMs, data warehouses, manager statements, and legacy systems to establish trusted data.

Drive creation and maintenance of investment golden records and authoritative datasets across the investment landscape.

Lead data migration and transformation activities, including data profiling, source-to-target mapping, validation, cleansing, and post-migration reconciliation.

Define and implement data-quality frameworks, controls, exception management processes, governance standards, and audit trails.

Perform hands-on business and data analysis, including SQL-based data validation, root-cause analysis, and review of investment-data outputs.

Partner with investment, operations, technology, and external stakeholders to translate business requirements into scalable data solutions.

Lead the implementation and ongoing enhancement of the Citco Document Service ingestion pipeline leveraging Azure Data Factory, Azure Functions, Snowflake, SharePoint, Microsoft Graph API, and related Azure services.

Identify opportunities to automate manual reconciliation, data-quality, and operational processes using Python, AI, and intelligent automation technologies.

Develop operational dashboards, reporting, KPIs, and governance metrics to monitor data quality, process Key competencies Bachelors or Masterefficiency, and delivery performance.

Key competencies

Bachelors or Masters degree in computer science, Information Systems, Engineering, MCA, or a related discipline.

Strong leadership and people-management skills with proven experience leading Business Analyst, Data Analyst, or Data Operations teams.

Deep understanding of private markets, fund investment data, fund structures, commitments, capital calls, distributions, NAV, valuations, cash flows, and performance metrics.

Expertise in investment-data reconciliation, data remediation, golden record creation, and multi-source data validation.

Proven experience managing complex data migration, transformation, and system implementation programs.

Strong business analysis capability, including requirements gathering, process mapping, stakeholder workshops, and functional specification development.

Advanced SQL skills with the ability to independently profile, analyze, validate, and troubleshoot large and complex datasets.

Hands-on experience with Snowflake, Azure Data Services, data warehouses/lakehouses, and modern data platforms.

Working knowledge of Python or similar scripting languages for data analysis, automation, and reconciliation activities.

Experience integrating enterprise platforms and document-processing solutions, including SharePoint, Microsoft Graph API, Citco, DealCloud, eFront, CEPRES, or comparable systems.

Strong problem-solving, analytical thinking, and root-cause analysis capabilities with exceptional attention to detail.

Excellent stakeholder management, communication, presentation, and executive reporting skills with the ability to bridge business and technology teams.

Continuous improvement mindset with experience leveraging automation, AI, or LLM-enabled solutions to enhance data operations and operational efficiency.