Head of Data Engineering

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 integration of AI-powered techniques into data quality, anomaly detection, and reporting workflows where they deliver measurable value

Requirements

• Extensive, hands-on expertise in Python for data engineering, pipeline development, and automation
• Deep proficiency in SQL and relational data modelling; experience with NoSQL systems and semi-structured data formats
• Proven experience architecting and delivering enterprise data platforms on Azure; Databricks experience strongly preferred
• Comprehensive understanding of data warehouse and Lakehouse patterns, ETL/ELT pipeline design, and dimensional modelling
• Sophisticated understanding of investment data domains — IBOR, risk reporting, performance attribution, and returns — with the ability to translate business requirements into reliable data products
• Demonstrated experience with data governance tooling, data cataloguing, and metadata management
• Familiarity with AI-driven development practices; exposure to MCP, LLM integration, or AI-augmented analytics is a meaningful differentiator
• Experience designing and governing REST API integrations, OAuth-based authentication, and event-driven data architectures
• Strategic ownership — brings a product mindset to data infrastructure; defines the vision and holds the platform to it
• Investment domain fluency — instinctively understands what IBOR data quality means to a portfolio manager, what a risk report demands of its underlying data, and why performance attribution requires ironclad accuracy
• Delivery excellence through partners — experienced leading technical outcomes through consulting firms and offshore teams; knows how to set standards, inspect work, and escalate with precision
• Rigorous analytical instincts — applies systematic diagnostic discipline to complex data issues; communicates findings and remediation plans with clarity to both technical and business audiences
• Institutional gravitas — operates comfortably at the intersection of technology and investment management; earns trust quickly with portfolio managers, risk officers, and senior leadership
• Composure in a demanding environment — CIFC operates with urgency on a fast-moving trading floor; this leader is calm, decisive, and reliable under pressure
• Curious technologist — self-motivated to stay current on AI, data tooling, and platform trends; doesn't wait to be assigned learning

Experience and Education

• Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent; advanced degree a plus
• 12+ years of progressive experience in data engineering, data architecture, or data platform leadership roles
• Demonstrable history of leading data initiatives at financial services firms; asset management or investment adviser experience is strongly preferred
• Proven track record owning and delivering enterprise data platforms — from strategy through production — in complex, multi-stakeholder environments
• Substantial experience managing and governing external consulting partners or offshore delivery teams
• Prior exposure to IBOR applications, OMS platforms, risk systems, and performance/returns reporting infrastructure is highly valued
• Experience operating at ED or MD level, or equivalent senior leadership scope, within a technology or data organization