Senior Associate, Data Management - Data & Technology Solutions

We are global private markets specialists delivering tailored investment solutions, advisory services, and impactful, data driven insights to the world’s investors. Leveraging the power of our platform and our peerless intelligence across sectors, strategies, and geographies, we help identify the advantages and the answers our clients need to succeed.

Position Overview:

Data Analytics & Technology Solutions (DATS) is StepStone’s unified data analytics and technology department. We build SPI by StepStone, the proprietary technology platform our clients use to navigate private markets, and we deliver the data solutions, automation, and analytics that teams across the firm use every day. The integrity of everything DATS produces depends on the data management processes that sit underneath it.

This role is responsible for the collection, ingestion, validation, and mapping of private markets data across a defined and growing set of business processes within the firm. In private markets, data rarely arrives in a format that is ready to use. This role will be responsible for data processes based on unstructured fund manager documents, structured data in formats that need to be translated into different formats, and direct data collection campaigns.

Further, the role will also oversee the consolidation and mapping of data records contained within the proprietary and third-party platforms used across the firm. This individual will maintain an intimate relationship with the data to establish and modernize processes through the strategic use of technology and AI, partnering with engineering, analytics, and product teams across DATS to replace manual effort with scalable, automated workflows while maintaining appropriate human-in-the-loop oversight.

The role carries direct management responsibility for a team of data management professionals and oversight of offshore and vendor capacity.

Essential Job Functions:

Owns the end-to-end design, execution, and quality of data management workflows within the team’s scope, from intake and extraction through validation, mapping, and release to downstream systems and clients

Establishes the control framework for data quality: accuracy and completeness standards, automated checks and exception queues, and accountability to defined SLAs

Leads the application of AI and automation across its data management processes, including data extraction, classification, entity resolution, and mapping, while evaluating technologies, designing human-in-the-loop workflows, and measuring accuracy gains and efficiency improvements against manual processes

Assesses current-state workflows to find the root causes of rework and error, and delivers redesigned processes with documented procedures, controls, and measurable throughput gains

Governs the data mapping framework that connects source data to StepStone’s enterprise data model, including taxonomies, entity hierarchies, identifiers, and the processes for proposing, approving, versioning, and maintaining mapping rules

Manages and develops a team across onshore, offshore, and vendor resources. Sets priorities and capacity plans and builds training and quality review programs

Partners with DATS engineering, analytics, and product teams to translate recurring operational pain into platform capability, writing clear requirements and following through to adoption

Serves as the escalation point for data quality issues raised across investment, finance, reporting, and client-facing teams, driving resolution to root cause rather than symptom

Defines, tracks, and reports operational KPIs across volume, cycle time, quality, cost, and automation, using performance trends to determine where the team should focus its next investments and improvement efforts

Education and/or Work Experience Requirements:

• Bachelor's degree in a relevant field
• 5 to 8+ years in data management, investment operations, or a comparable data-intensive function, preferably within private markets or alternative asset management
• Demonstrated experience designing and implementing data workflows at scale, with a track record of specific processes automated and the gains that resulted
• Direct people management experience, including managing offshore or vendor delivery

Hands-on experience applying technology (and ideally AI) to operational data problems, including document extraction, data classification, mapping, and quality controls to ensure reliability

Working knowledge of private markets data, including fund structures, cash flows, performance reporting, and portfolio company financials

Required Knowledge, Skills, and Abilities:

Process design skills, including the ability to look at a manual workflow, see the version that should exist, and build the plan to get there

Genuine technical fluency with the ability to read and write SQL, reason about data models and APIs, work with modern data platforms (e.g., Snowflake, Power BI, Power Platform), and hold a credible conversation with engineers

• Practical command of the current AI tooling landscape and honest judgment about where it is reliable enough to put in front of client-facing data
• Exceptional attention to detail, paired with the discipline to build controls that catch errors systematically rather than relying on individual vigilance
• Strong analytical and critical thinking skills; able to structure ambiguous problems and cut through to root causes
• Clear written and interpersonal communication, with the ability to represent the function credibly with senior stakeholders
• Ability to work independently and perform under deadlines in a dynamic environment