Data Migration Analyst
Short-Term Contract | Approx. 30 Days | Day Rate – Outside IR35 | Remote (UK)
About the Role
Company is building a brand-new internal contract hub to replace its legacy contract tracking tools. Ahead of the technical build, they need a data-savvy analyst to lead a time-boxed project: extracting, profiling, and migrating their entire back-catalogue of executed contracts into the new repository – cleaned, de-duplicated, and mapped against a proper metadata schema.
This is a data quality and data engineering problem as much as anything else. You’ll be working across multiple disconnected sources – eSignature platforms, a legacy SQL database, SharePoint, and old ticketing systems – to build a single, reconciled, trustworthy dataset.
What You’ll Be Doing
- Source discovery and profiling – inventory every source system, produce actual record/document counts, and assess data quality, access routes, and risk (week one deliverable)
- Scripted extraction – write and run scripts (SQL and beyond) to pull documents and structured/unstructured metadata in bulk from eSignature platforms, a legacy SQL database, SharePoint/shared drives, and a contract management system
- Data cleansing and de-duplication – consolidate everything into a single staging dataset, applying a documented, defensible rule for which record wins where duplicates exist
- Metadata schema and mapping – build and populate a metadata register against agreed core fields (contract type, counter party, entity, effective/end/renewal dates, value, governing document reference, source system), explicitly flagging gaps rather than inferring or leaving blank
- Validation via sample migration – run a sample batch into the live repository to test and refine the mapping logic and transformation rules before scaling up
- Full-scale load – execute the bulk migration into the new repository structure, correctly mapped against the agreed schema and naming convention
- Documentation and handover – produce a clear data lineage/handover note: what was migrated, what couldn’t be and why, anomalies parked for decision, and the scripts and logic used, so the pipeline is repeatable and auditable
What You’ll Need
- Strong data extraction and scripting skills (SQL plus a scripting language such as Python) – this is a scripted, repeatable-process role first, with manual review reserved for genuine exceptions
- Experience with data profiling, cleansing, de-duplication, and metadata/schema mapping across disparate, messy sources
- Comfort reconciling structured and unstructured data from multiple systems into one clean data set
- A methodical, detail-obsessed approach – this role is about data accuracy, traceability, and repeatability, not shortcuts
- Good judgement on when to escalate rather than infer, especially with ambiguous, incomplete, or sensitive records
- Experience handling confidential or commercially sensitive data professionally and securely
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