Data Mapping Engineer

Company: Data Inc

Location: London

Posted: April 11th, 2026

Overview

Data Mapping Engineer – To define the source and target object modelling and lead the data mapping between source and target systems

Contract Type: Fixed Term Contract (FTC)

Duration: 12 months

Start Date: Jan 2026

Current day rate and contract type:

Business Context

This is a greenfield data mapping exercise — no validated source-to-target mapping specification currently exists.

The role requires designing the object model alignment between legacy platforms (RIBS and Milvis) and the target Avaloq Opus instance, which is still being built out for the CI business unit.

The migration is complicated by 40+ years of legacy client, banking, and custody data, requiring strong data modelling and interpretation skills.

Summary

We require someone who has lived and breathed, been hands on in leading and pulling together a data migration mapping specification / document for a wealth migration platform. Usual legacy platform migration to new target platform and the complication that brings with having data that is 40yrs old on the legacy side. Mapping spec, object modelling, data modelling experience. Avaloq and wealth management experience would be advantageous. Clear and crisp stakeholder management and the ability to drive a decision.

Required Experience/Skills

Experience mapping into non-mature or in-build platforms, where target data structures are evolving and require architectural interpretation.

Ability to analyse, rationalise, and model poorly structured or inconsistent legacy datasets spanning multiple decades.

Proven ability to drive structural decisions and achieve stakeholder alignment where multiple interpretations or source-of-truth options exist.

Comfortable presenting and defending mapping and modelling proposals to architecture, IT, business SMEs, and Avaloq teams.

Competent SQL user capable of profiling data, validating mapping logic, and supporting defect investigations (not as a developer, but confident enough to interrogate datasets).

#J-18808-Ljbffr
Apply Now