Fund Accounting- Data analyst

Description for Internal Candidates

• Experience in Fund Accounting, asset servicing, or investment operations.
• Familiarity with NAV calculation, positions, transactions, and accounting hierarchies.
• Experience working with:
• Thirdparty accounting platforms
• Vendorprovided data feeds
• Canonical or enterprise data models

Project Description:

The Fund Accounting Data Project ingests, rationalizes, and publishes fund accounting data from firstparty and thirdparty Fund Accounting systems into a centralized Data Platform.

The platform supports two primary outcomes:

• A clientfacing portal with analytics and data visualizations
• The Core Accounting Model, acting as the internal canonical representation of accounting data

The initiative involves:

• SQL Serverbased source systems
• APIbased vendor data feeds
• Cloudbased processing and transformation (Databricks)
• High requirements for data accuracy, auditability, and lineage

Role Objective Provide a Technical Analyst who can operate within a technical delivery team to define and manage data requirements for ingestion and conversion from Fund Accounting source systems. The analyst is responsible for translating business and accounting concepts into clear, unambiguous technical data artifacts, including detailed documentation of data mappings and transformations. Role Context

Embedded within a data platform / data engineering delivery team.

Works daily with:

• Data engineers
• Platform engineers
• Accounting SMEs
• Product and delivery leads

Operates in an Agile delivery model with incremental releases.

Primary focus is data correctness, consistency, and usability downstream.

Core Responsibilities (What They Will Do)

• Elicit and clarify fund accounting and data requirements from accounting SMEs and business stakeholders.
• Analyze sourcesystem data structures, schemas, and extracts.
• Define and document:
• Sourcetotarget data mappings
• Transformation and conversion rules
• Data standardization logic
• Produce and maintain:
• Technical data requirements
• Data catalogs
• Data dictionaries
• Definitions of canonical data elements
• Translate business and accounting requirements into technically actionable specifications for data ingestion pipelines.
• Partner closely with data engineers to validate mappings, transformations, and assumptions.
• Use SQL to:
• Profile source data
• Validate transformation logic
• Support reconciliation and data quality checks
• Support downstream consumers by ensuring data is fit for visualization and core accounting model usage.

Explicit NonResponsibilities (Important for Profile Filtering)

• Not a project manager or delivery lead.
• Not a visualization or BI developer.
• Not a data engineer writing ingestion pipelines.
• Not a purely functional BA without handson data analysis capability.

Required Experience (NonNegotiable)

• 5+ years as a Technical Analyst, Data Analyst, or Technical Business Analyst in datacentric initiatives.
• Strong SQL skills; able to independently analyze large and complex datasets.
• Direct experience with data ingestion, transformation, or migration projects.
• Experience defining sourcetotarget mappings and data conversion logic.
• Proven track record working closely with engineering teams in Agile environments.
• Ability to operate effectively with incomplete, inconsistent, or evolving source data.

Preferred Background (Strong Signals)

• Experience in Fund Accounting, asset servicing, or investment operations.
• Familiarity with NAV calculation, positions, transactions, and accounting hierarchies.
• Experience working with:
• Thirdparty accounting platforms
• Vendorprovided data feeds
• Canonical or enterprise data models
• Exposure to data governance concepts such as data lineage, ownership, and quality controls.

Success Criteria (How We Will Judge Fit)

A successful Technical Analyst on this project will:

• Produce clear, implementationready data specifications trusted by data engineers.
• Identify data quality issues and inconsistencies early in the ingestion process.
• Reduce rework by eliminating ambiguity in mappings and transformation logic.
• Ensure consistent data definitions across multiple source systems.
• Enable accurate downstream reporting and accounting model consumption.

Seniority Guidance

• MidtoSenior level individual contributor.
• Expected to work independently with minimal oversight.
• Must proactively drive clarification, documentation, and resolution of data issues.