Data Specialist

Job summary

Own the meaning, grain, quality, and fitness-for-use of data products and assets, including foundational operational data objects and composite KPIs. Partner with product, analytics, modeling, engineering, and value-stream teams to define, validate, document, and publish trusted data assets, using AI to accelerate delivery while remaining accountable for production decisions.

Job details

Job Title -Data Expert (Data Product / Data Asset) Location: Canada (remote) Length: 3-9 month contract to hire Full-time · Leadership embed · Data products & KPIs Defines and shapes iX360 data products and data assets — from basic lake objects (purchase orders, job orders, delivery orders, ASNs) through composite KPIs built from those elements. Not an MDM Data Steward: stewards own source masters (account, material, supplier); you consume well-known stewarded sources and produce trusted lake/analytics assets. Embeds by team; Channel Insights first. AI delivery expectation: Use AI copilots/agents daily to accelerate discovery, build, test, and documentation. Optimize for cycle time and cost-to-outcome vs legacy delivery. Embed automation into quality gates. You remain accountable for production decisions. What You’ll Do Own the meaning, grain, and fitness-for-use of iX360 data products — basic lake objects and the complex KPIs composed from them. Partner with CDP PO on Channel Insights outcomes; translate business questions into asset definitions engineers and modelers can build. Specify contracts for objects such as purchase orders, job orders, delivery orders, ASNs, and related HVAC channel/service facts — freshness, keys, quality rules, consumer SLAs. Design composite KPI logic (definitions, denominators, exceptions) with Analytics Lead; refuse vanity metrics without lineage to basic elements. Work loosely with MDM/domain Data Stewards only where needed — source masters they own should already be well known; escalate gaps rather than become the steward. Embed with value-stream teams (Insights first; then Claims, CC, Marketing as needed) so data products ship inside discovery/delivery — not a central data ticket queue. Partner with Data Modeler (canonical shape) and Data Engineer (pipelines) without owning their craft; you own whether the asset answers the business problem. Use AI to draft KPI trees, mapping hypotheses, and data-product docs; verify with sample queries and domain SMEs before production publish. Publish living data-product catalogs and “how to use this KPI” guidance so PMs and field leaders consume assets correctly. What You Bring 7+ years in data products, analytics engineering, BI architecture, or domain data expertise for manufacturing / distribution / channel / service Proven ownership of lake or warehouse assets and composite KPI suites used in production decisions — not only MDM stewardship or pure ETL tickets Fluent in grain, slowly changing dimensions, identity, and KPI composition; can explain a metric from executive slide to source fields Comfortable embedding with PMs, modelers, engineers, and analysts; ships definitions and validated samples, not governance theater Exposure to Data Lake / enterprise lakehouse patterns and Salesforce Data 360 (or equivalent CDP) a strong plus Uses AI as a force multiplier for discovery and documentation; validates every definition with data Education & Experience Bachelor’s in quantitative, engineering, or business field (or equivalent); domain HVAC/manufacturing/channel experience preferred About Dexian: Dexian stands at the forefront of Talent + Technology solutions with a presence spanning more than 70 locations worldwide and a team exceeding 10,000 professionals. As one of the largest technology and professional staffing companies and one of the largest minority-owned staffing companies in the United States, Dexian combines over 30 years of industry expertise with cutting-edge technologies to deliver comprehensive global services and support. Dexian connects the right talent and the right technology with the right organizations to deliver trajectory-changing results that help everyone achieve their ambitions and goals. To learn more, please visit https://dexian.com/. Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status. Note: Dexian Canada will, on request, provide accommodations for disabilities to support

What you’ll do

Own the meaning, grain, quality, and fitness-for-use of data products and assets, including foundational operational data objects and composite KPIs. Partner with product, analytics, modeling, engineering, and value-stream teams to define, validate, document, and publish trusted data assets, using AI to accelerate delivery while remaining accountable for production decisions.

Requirements

Requires 7+ years of experience in data products, analytics engineering, BI architecture, or domain data expertise, with proven ownership of production lake or warehouse assets and composite KPIs. Candidates should be fluent in data grain, slowly changing dimensions, identity, and KPI composition; a relevant bachelor's degree or equivalent is expected, with HVAC, manufacturing, or channel experience preferred.

Listed skills

• Data analysis · Preferred
• Production · Preferred
• KPI · Preferred
• Teams · Preferred
• Time · Preferred
• Warehouse · Preferred
• contracts · Preferred
• Documentation · Preferred
• Leadership · Preferred
• Mapping · Preferred
• Salesforce · Preferred
• Organization · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Product Ownership
• Data Asset Definition
• KPI Design
• Data Quality
• Data Modeling
• Data Lakehouse
• Analytics Engineering
• Business Intelligence
• Slowly Changing Dimensions
• Data Identity Resolution
• Salesforce Data 360
• AI Copilots and Agents
• Data Cataloging
• Stakeholder Collaboration
• Manufacturing and Distribution Data

Job areas

• Data & Analytics
• Technology
• Management & Leadership
• Manufacturing
• Logistics

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