CIFC OVERVIEW
Founded in 2005, CIFC Asset Management LLC (together with its affiliates, “CIFC” or the “Firm”) is a global credit manager with $47 billion in assets under management as of December 31, 2025. CIFC focuses across multiple disciplines including CLOs, structured credit, corporate credit, and opportunistic credit, as well as direct lending. Headquartered in New York, and serving over 400 investors globally, we have approximately 200 employees with over 95 investment professionals averaging 14 years of credit experience. We are guided by a rigorous investment process, with an acute focus on downside risk protection and bottom-up fundamental credit research applied across our disciplines. For more information, please visit CIFC’s website at www.cifc.com.
Position Summary:
CIFC is seeking an accomplished Head of Data Engineering to own the strategy, architecture, and delivery of the firm's enterprise data platform. This is a senior leadership role within the Information Technology organization, reporting to the Head of Application Development. The successful candidate will bring a distinguished track record of leading data initiatives at financial services firms — ideally an asset manager or investment adviser — with deep fluency in investment data domains including IBOR, risk reporting, performance attribution, and returns analytics. Working primarily through a consulting-partner-led delivery model, this leader will serve as the internal technical authority and strategic owner — setting direction, governing architecture decisions, and ensuring that data products are built to institutional standards of quality, reliability, and auditability. This is a high-visibility role with direct impact on firmwide reporting, compliance, and investment decision-making
Responsibilities:
Data Platform Strategy & Architecture
- Define and own the multi-year strategy for CIFC's enterprise data platform, establishing authoritative data stores that serve as the golden source for firmwide reporting, analytics, and AI applications
- Architect scalable, governed data pipelines and Lakehouse infrastructure (Azure / Databricks) that consolidate data from investment systems, third-party vendors, and operational sources
- Establish and enforce data architecture standards, modelling best practices, and platform governance frameworks across all data domains
- Evaluate and make build-vs-buy recommendations on data tooling, pipeline frameworks, and storage technologies — balancing institutional requirements with long-term maintainability
Investment Data & Domain Ownership
- Serve as the internal subject matter expert on investment data domains — with particular depth in IBOR (Investment Book of Record), risk reporting, performance measurement, and returns attribution
- Partner with Portfolio Management, Risk, and Finance to understand data consumption patterns, SLA requirements, and the downstream impact of data quality on investment and reporting processes
- Ensure data products meet the rigorous accuracy and timeliness standards required for regulatory reporting, client reporting, and investment decision support
- Develop a deep working knowledge of CIFC's application landscape — including relevant IBOR, OMS, risk, and performance systems — and translate that understanding into coherent data integration strategies
Delivery & Consulting Partner Governance
- Lead and govern the firm's data engineering delivery in partnership with external consulting partners — defining scopes of work, setting quality standards, and maintaining technical oversight of partner deliverables
- Act as the primary technical counterpart to consulting partners: reviewing designs, validating implementations, and ensuring alignment with CIFC's architectural principles
- Drive accountability for delivery milestones, data quality outcomes, and platform health — escalating and resolving issues with urgency and precision
Data Quality, Governance & Observability
- Champion a firm-wide culture of data quality — establishing lineage tracking, data cataloguing, and observability practices that give stakeholders confidence in every data product
- Design and implement data governance frameworks including ownership, classification, access controls, and audit trails, in alignment with compliance and regulatory obligations
- Proactively identify, investigate, and remediate data integrity issues across the platform — applying strong analytical and debugging skills to isolate root causes and prevent recurrence
AI & Emerging Technology
- Collaborate with the Business Strategy & AI Transformation team to ensure the data platform is AI-ready — providing clean, structured, and semantically rich data to support LLM-driven applications and analytical workflows
- Maintain a strong working awareness of the latest developments in LLMs, AI-driven analytics, and data engineering tooling; bring forward relevant opportunities and experiments to the leadership team
- Drive the