Data Cleansing & Reconciliation Specialist – Investment Data Transition | London, UK | Hybrid

Strike IT • London, England, GB • 1d ago

We’re partnering with a leading investment organisation embarking on a major fund transition programme and are seeking a Data Cleansing & Reconciliation Specialist to support a large-scale data migration and validation effort.

This role will focus on ensuring the accuracy and completeness of investment-related data across multiple funds, working with stakeholders across data, operations, and technology teams to prepare high-quality datasets for integration into core systems.

INSISE IR35

Key Responsibilities

Cleanse, reconcile and validate investment data across multiple portfolios to ensure consistency with target data models and reporting standards.

Prepare and transform datasets for upload to internal systems, ensuring accuracy across historical valuations, transactions, and performance records.

Identify and resolve data quality issues, investigating gaps or anomalies in valuation, transaction, and position data.

Collaborate with administrators, custodians, and market data providers to confirm the integrity and alignment of data feeds.

Create and maintain a comprehensive investment inventory covering both private and public market holdings, including detailed asset hierarchies and look-through structures.

Support the ongoing integration of new data sources and ensure forward-looking data feeds are mapped correctly to operational and performance systems.

Experience & Skills

Proven track record in data cleansing, reconciliation, and validation within asset management, pension funds, or investment operations.

Strong knowledge of ABOR / IBOR principles, and experience reconciling valuation and transaction data.

Experience handling both private market and public market investment data, including fund-of-funds and real asset structures.

Familiarity with working alongside custodians, fund administrators, and data vendors.

High level of attention to detail, analytical capability, and comfort managing complex datasets.

Strong Excel skills and an understanding of data mapping, system uploads, and reconciliation processes.

Excellent communication and documentation skills, with the ability to collaborate effectively across project and operational teams.

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