Data Consultant

Fusion Risk Management•,

2d•$120,000 - $145,000

About The Position

The Data Consultant is a customer-facing expert who helps customers get data into and flowing through the Fusion platform. The role involves understanding customers’ data, where it resides, and how it should move into Fusion, then recommending an approach that helps them get more value from the platform. The position combines data integration expertise with consulting skills. The Data Consultant advises customers on data strategy, designs and supports integrations suited to their environments, and helps implementation teams deliver reliable, secure, and sustainable data solutions. The role works closely with customers, implementation consultants, Technical Architects, Customer Success, Support, and Product, serving complex and resilience-critical organizations.

Requirements

Strong understanding of data integration concepts, including REST APIs, file-based and bulk loads, ETL/ELT, data mapping and transformation, and event-driven or scheduled integrations.
Experience working with data from enterprise systems such as HR, ITSM, CMDB, GRC, finance, and risk and resilience tools.
Strong data analysis, quality, and validation skills, including the ability to identify and resolve data issues.
Working knowledge of SQL and data modeling.
Consulting skills, including discovery, requirements gathering, solution recommendation, and managing customer expectations.
Strong verbal and written communication skills, including the ability to explain technical data concepts to executive and non-technical audiences.
Ability to facilitate workshops and influence customer decisions on data approach and priorities.
Strong problem-solving, organization, and project management skills, with the ability to manage multiple engagements at once.
Ability to learn a new enterprise platform quickly.
Familiarity with AI tools and willingness to incorporate them into day-to-day work.
Agile methodology experience, such as Scrum or Kanban.
Bachelor’s degree in Information Systems, Computer Science, Data Management, or a related field, or equivalent experience.
At least 5 years of experience in data integration, data management, or technical consulting, including customer-facing delivery.
Experience in enterprise B2B software or professional services environments.

Nice To Haves

Scripting or API tooling experience, such as Python or Postman.
Experience with the Fusion platform or with an enterprise SaaS platform implementation in risk, resilience, GRC, or business continuity.
Experience with an integration platform or middleware tool, such as MuleSoft, Boomi, Workato, or Azure Integration Services.
Salesforce certification, such as Platform App Builder or Platform Developer.

Responsibilities

Consult with customers, engagement managers, and solution leads to understand business goals, data sources, and data quality, and recommend how to get data flowing into Fusion.
Assess customer data readiness, including source systems, ownership, quality, and refresh needs, and document a path from the current to target state.
Advise customers on data-loading methods, including bulk file loads, APIs, scheduled and automated integrations, middleware, iPaaS tools, and AI, and recommend the best fit.
Design data models, mappings, and load strategies that preserve data integrity and support reporting, analytics, and downstream use cases.
Configure, build, and support integrations with customer systems, working with customer technical teams as needed.
Lead customer data workshops and working sessions, explaining options and trade-offs in clear, non-technical terms.
Troubleshoot data-load and integration issues and resolve root causes with customers, Support, and Product.
Advise and mentor implementation consultants on data best practices, templates, and integration approaches.
Create repeatable data integration patterns, templates, and guides, and capture lessons learned to improve delivery across engagements.
Help customers establish data governance and ongoing data maintenance practices.
Share field insights with Product and Engineering to inform platform and integration roadmap priorities.
Use AI tools to improve efficiency in data mapping, analysis, validation, and troubleshooting, and share useful practices with the team.