Data Migration Engineer

• Lead a time-boxed data migration project to extract, profile, clean, de-duplicate, and migrate executed contracts into a new internal repository
• Inventory every source system, produce record and document counts, and assess data quality, access routes, and risk
• Write and run scripts to pull documents and structured or unstructured metadata in bulk from multiple systems
• Consolidate source data into a single staging dataset and apply documented rules for duplicate resolution
• Build and populate a metadata register against agreed core fields, explicitly flagging gaps rather than inferring or leaving blanks
• Run a sample migration to test and refine mapping logic and transformation rules before scaling up
• Execute the full bulk migration into the new repository structure using the agreed schema and naming convention
• Produce clear documentation and handover notes covering what was migrated, what could not be migrated and why, anomalies, and the scripts and logic used

Technologies:

• Python
• SQL
• SharePoint

More:

We are building a brand-new internal contract hub to replace our legacy contract tracking tools. This is a short-term contract of approximately 30 days on a day-rate basis, outside IR35, and remote within the UK. You will work across multiple disconnected sources, including eSignature platforms, a legacy SQL database, SharePoint, and old ticketing systems, to create a single reconciled and trustworthy dataset. This role is focused on data quality and data engineering, with a strong emphasis on traceability, repeatability, and auditable migration. If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.

• Strong data extraction and scripting skills, including SQL and a scripting language such as Python
• 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 focused on data accuracy, traceability, and repeatability
• 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