• Location: No Location Set
• Type: Contract
• Job #35930

Technical Business Analyst – Syndigo / PIM / MDM

Location: Toronto-based; remote to hybrid. Travel to a client site, approximately 1–2 times per month may be required (expenses paid). Must work Eastern Time business hours.
Contract: 2 months to start, with potential extensions
Hours: 40 per week

Key requirement: Hands-on Syndigo implementation experience will be a significant factor in selection. Candidates with strong Syndigo experience are likely to be preferred over those whose MDM experience is limited to Stibo STEP or other platforms.

About the Role

Our client designs, implements, manages, and maintains complex ecommerce and master data solutions for large enterprises. Its work combines technical expertise with business context to solve data and commerce challenges for enterprise and mid-market organizations.

This hands-on Technical Business Analyst role bridges business requirements, technical design, and data strategy. You will own discovery, requirements documentation, data architecture, and platform configuration for PIM/MDM initiatives. The team works with enterprise platforms including Syndigo, Stibo STEP, Akeneo, and cloud-native solutions.

Syndigo experience is especially important for this assignment. Experience with other enterprise MDM platforms is valuable, but candidates who have implemented Syndigo will be more competitive.

You will work as a co-equal lead alongside another BA, with full ownership of your workstreams. You should be able to learn new platform capabilities quickly, assess requirements critically, and use AI tools where appropriate while maintaining sound data governance.

Approximate time split: 40% discovery and requirements; 40% technical design and data work; 20% UAT, validation, and handover.

Responsibilities

• Run client workshops and translate business requirements into structured, testable user stories. Use GenAI tools to draft and iterate where appropriate, then critically validate the output.
• Flag scope risks early and recommend realistic alternatives when timelines, budgets, or data quality conflict with requirements.
• Profile and audit legacy data, inventory data sources, identify quality issues, and design transformations for the target platform.
• Design and implement data governance and quality rules, including stewardship models, hierarchies, attribute governance, and the master data lifecycle.
• Own data migrations end to end, including the approach, mapping, ETL runbooks, cutover validation, and rollback procedures.
• Maintain a requirements traceability matrix (RTM) and manage scope changes through formal change control.
• Write and execute UAT scripts, validate results, and manage defects through sign-off. Use AI-assisted test generation where appropriate.
• Demo completed features and user stories, explaining technical constraints and trade-offs in business terms.
• Document the system and train client teams on MDM platform capabilities and governance processes.
• Facilitate stakeholder workshops and manage expectations across business, IT, data governance, and vendor teams.
• Become a team expert on the assigned MDM platform, including new features and vendor releases.
• Manage vendor escalations and participate in Agile sprint ceremonies.

Must-Have Skills

MDM and Data Experience

• Hands-on Syndigo implementation experience is strongly preferred and will be a key differentiator in selection.
• 7–10+ years in business analysis, requirements gathering, or data strategy for MDM, PIM, data integration, or enterprise information management projects.
• 4+ years implementing enterprise MDM platforms such as Syndigo, Stibo STEP, Akeneo, Talend, or tier-one equivalents. Able to learn new platforms quickly and apply MDM principles across vendors.
• Hands-on experience with hierarchies, attribute management, data quality rules, workflows, integration patterns, and stewardship models.
• Proven experience planning and executing data migrations, including legacy profiling, ETL design, mapping, transformation logic, validation, and cutover risk management.
• Deep knowledge of master data governance, the data stewardship lifecycle, and operating model design.

Technical and Analytical Skills

• Advanced Excel skills, including mapping matrices, data profiling, pivot tables, validation rules, and VLOOKUP/INDEX-MATCH.
• Ability to read and interpret SQL queries and work with technical teams on data extracts and ETL logic.
• Experience with Visio, Lucidchart, or similar tools for data flow and system architecture diagrams.
• Experience authoring RTMs, functional specifications, and UAT scripts with clear acceptance criteria.
• Comfortable using GenAI tools such as ChatGPT or Claude to draft requirements and documentation, while critically validating the output.
• Understands where AI-powered data quality and profiling tools can improve efficiency, as well as their limitations around accuracy and data privacy.

Communication and Problem-Solving

• Excellent written and verbal communication; able to explain complex data concepts and constraints to business and technical audiences.
• Strong facilitation and presentation skills, including with senior stakeholders; comfortable managing pushback.
• Critical thinker who challenges faulty assumptions, recognizes MDM anti-patterns, and advocates for sound governance.
• Independent and effective in a matrix environment, with availability during Eastern Time business hours.
• Scrum/SAFe certification or equivalent Agile fluency; familiar with Jira or Azure DevOps.

Nice to Have

• Hands-on experience with two or more MDM platforms, such as Syndigo, Stibo STEP, Akeneo, Talend, SAP MDG, or Informatica.
• Post-go-live support experience, including runbooks, troubleshooting, mentoring client teams, and defining L1/L2 support.
• Experience designing data stewardship or governance operating models or change management programs.
• Exposure to enterprise data platforms such as data lakes, Snowflake, BigQuery, or MDaaS.
• Familiarity with prompt engineering, LLM-assisted documentation, or AI governance in data contexts.
• Understanding of regulatory and audit requirements such as GDPR, data lineage, and consent management.