QIMA’s rapid growth has added complexity in data, systems, processes, and management structures. Successful integration requires close collaboration between technical, commercial, and core business teams. This role is responsible for driving that collaboration.
The Technical Project Manager, Commercial Integrations is an individual contributor responsible for the end-to-end integration of data, systems, and operational processes from acquired companies into QIMA's core infrastructure. You will own workstreams from initial data discovery and process mapping, through to production-ready pipelines and process handover, coordinating across legal, finance, commercial, and technical stakeholders. This is a mid-level role requiring engineering rigour and commercial fluency in equal measure: genuinely at home with data, and equally able to explain what you are doing and why it matters to people who will never open a database.
Technical Project Management
- Own project plans, timelines, risk registers, and status reporting for all active integration workstreams; escalate blockers and business decisions proactively.
- Maintain integration documentation, decision logs, and handover notes that enable teams to own the output once integration is complete.
Stakeholder Management & Communication
- Coordinate across Legal, IT, Finance, Sales, Marketing, and Revenue Operations to gather requirements, identify dependencies and handoffs, secure milestone sign-off, and manage competing priorities.
- Translate complex data processes into clear, accessible language for non-technical stakeholders at all seniority levels.
M&A Data Integration
- Lead post-acquisition data integration workstreams: discovery, profiling, schema mapping, matching, cleansing, and migration from acquired entities into QIMA systems.
- Define integration plans with clear milestones, dependencies, and acceptance criteria; identify data quality or process issues early and drive well communicated remediations.
- Validate data integrity across source and target systems at each stage; facilitate knowledge-extraction with acquired company experts before systems are decommissioned.
Data Engineering & Automation
- Build or coordinate data pipelines and ETL processes; apply AI and machine learning tooling to accelerate data ingestion, deduplication, and anomaly detection.
- Design automated quality checks that reduce manual validation effort without compromising accuracy.
Master Data Management & Governance
- Apply MDM principles to align acquired data with QIMA master data standards; define ownership, stewardship rules, and lineage documentation for integrated datasets.
- Navigate data protection and privacy requirements throughout integration, ensuring GDPR compliance while preserving data usability for analytics and AI applications.
