Fund Accounting- Data analyst

Description for Internal Candidates\n\nExperience in Fund Accounting , asset servicing, or investment operations.\nFamiliarity with NAV calculation, positions, transactions, and accounting hierarchies.\nExperience working with:\nThird‑party accounting platforms\nVendor‑provided data feeds\nCanonical or enterprise data models\n\nProject Description:\nThe Fund Accounting Data Project ingests, rationalizes, and publishes fund accounting data from first‑party and third‑party Fund Accounting systems into a centralized Data Platform .\nThe platform supports two primary outcomes:\nA client‑facing portal with analytics and data visualizations\nThe Core Accounting Model , acting as the internal canonical representation of accounting data\nThe initiative involves:\nSQL Server‑based source systems\nAPI‑based vendor data feeds\nCloud‑based processing and transformation (Databricks)\nHigh requirements for data accuracy, auditability, and lineage\n\nRole 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\nEmbedded within a data platform / data engineering delivery team.\nWorks daily with:\nData engineers\nPlatform engineers\nAccounting SMEs\nProduct and delivery leads\nOperates in an Agile delivery model with incremental releases.\nPrimary focus is data correctness, consistency, and usability downstream.\nCore Responsibilities (What They Will Do)\nElicit and clarify fund accounting and data requirements from accounting SMEs and business stakeholders.\nAnalyze source‑system data structures, schemas, and extracts.\nDefine and document:\nSource‑to‑target data mappings\nTransformation and conversion rules\nData standardization logic\nProduce and maintain:\nTechnical data requirements\nData catalogs\nData dictionaries\nDefinitions of canonical data elements\nTranslate business and accounting requirements into technically actionable specifications for data ingestion pipelines.\nPartner closely with data engineers to validate mappings, transformations, and assumptions.\nUse SQL to:\nProfile source data\nValidate transformation logic\nSupport reconciliation and data quality checks\nSupport downstream consumers by ensuring data is fit for visualization and core accounting model usage.\nExplicit Non‑Responsibilities (Important for Profile Filtering)\nNot a project manager or delivery lead.\nNot a visualization or BI developer.\nNot a data engineer writing ingestion pipelines.\nNot a purely functional BA without hands‑on data analysis capability.\nRequired Experience (Non‑Negotiable)\n5+ years as a Technical Analyst, Data Analyst, or Technical Business Analyst in data‑centric initiatives.\nStrong SQL skills; able to independently analyze large and complex datasets.\nDirect experience with data ingestion, transformation, or migration projects.\nExperience defining source‑to‑target mappings and data conversion logic.\nProven track record working closely with engineering teams in Agile environments.\nAbility to operate effectively with incomplete, inconsistent, or evolving source data.\nPreferred Background (Strong Signals)\nExperience in Fund Accounting , asset servicing, or investment operations.\nFamiliarity with NAV calculation, positions, transactions, and accounting hierarchies.\nExperience working with:\nThird‑party accounting platforms\nVendor‑provided data feeds\nCanonical or enterprise data models\nExposure to data governance concepts such as data lineage, ownership, and quality controls.\nSuccess Criteria (How We Will Judge Fit)\nA successful Technical Analyst on this project will:\nProduce clear, implementation‑ready data specifications trusted by data engineers.\nIdentify data quality issues and inconsistencies early in the ingestion process.\nReduce rework by eliminating ambiguity in mappings and transformation logic.\nEnsure consistent data definitions across multiple source systems.\nEnable accurate downstream reporting and accounting model consumption.\nSeniority Guidance\nMid‑to‑Senior level individual contributor.\nExpected to work independently with minimal oversight.\nMust proactively drive clarification, documentation, and resolution of data issues.