Role Description Are You a Highly Organized Person Who Can Speak 'Data,' Write Technical Documents in Perfect English, and Manage Important Projects to Success on Time? - Play a crucial role in streamlining our data operations. - Act as the primary filter for communications and data project tracking. - Manage the end-to-end flow of our data initiatives. - Triage complex emails to ensure every meeting results in documented, actionable data requirements. - Serve as a "second brain" for the team, knowing the status of every data request. - Ensure every team member is informed and held accountable. Responsibilities - Inbox Triage: Manage email threads, identifying high-priority data requests and answering inquiries on behalf of the team. - Meeting Synthesis & Insights: Attend meetings regarding data analysis; capture complex details and translate them into clear, actionable next steps and summaries. - Project Accountability: Proactively follow up with team members to ensure deadlines are met and projects stay on track. - Data Documentation: Create and maintain clear records of analytics requests, meeting outcomes, analytic specs, and data requirements. - Data Literacy & Quality Control: Review post-meeting data results/reports to ensure alignment with decisions made during discussions and flag inconsistencies. - Pre-Meeting Briefing & Intel: Review all upcoming meeting agendas and stakeholder requests in advance to brief the Lead Analyst. Qualifications - Proven Experience: 1-2 years experience in Executive Assistance, Project Management, or as a Junior Data Analyst, preferably in a fast-paced environment. - Strong Communication Skills: Excellent verbal and written communication skills, while being firm about deadlines and proactive about project needs. - Strategic Synthesis: Ability to identify the 3–4 most critical analytical takeaways in complex meetings. - Attention to Detail: A "detective" mindset for reviewing reports and briefing the Lead Analyst. - Adaptability: Ability to work remotely and manage multiple projects simultaneously with flexibility. - Cultural Fit: Understanding of and alignment with the company’s values and culture. Benefits - Rate: $8-15 per hour (Proposed rate for the role based on the market rate). Company Description Interested? Apply now to join our team and help as a strategic right hand to our Data Lead that will contribute to our company’s success. We look forward to reviewing your application and working with you to elevate our team!

• Lead the global rollout of Gong Forecasting across the full AE organization, driving platform adoption, building executive forecast dashboards for CRO-level visibility, and designing AE/RD 1:1 coaching dashboards for Sales Leadership • Own and evolve the Sigma Computing reporting ecosystem—including Activity Analytics, EOQ Retro, Metrics That Matter, and the GTM Reporting Catalog—replacing manual spreadsheet workflows with scalable, governed BI solutions • Apply an AI-first approach to analytics: lead a formal Sigma AI POC, identify high-impact use cases where AI reduces time-to-answer for Sales Leadership, and deliver a strategic FY27 roadmap for AI-driven self-service analytics built on Snowflake AI • Architect and execute the Salesforce Opportunity Split framework end-to-end—from technical requirements and Finance sign-off through pilot deployment, downstream impact analysis, and full Snowflake/Sigma data pipeline parity • Drive GTM Data Governance by owning the cross-functional Data Dictionary, relaunching the Reporting Council, and formalizing the KPI sign-off and metric codification process with Data Engineering • Define and document the strategic Reporting Strategy vision, including target-state outcomes, Gold Standard certified reports, and a scalable self-service analytics framework • Partner with Sales Enablement and Field Operations to build training programs, enablement materials, and adoption strategies that drive lasting behavior change across the revenue organization • Conduct deep-dive analyses to surface pipeline health trends, forecast risks, and performance gaps—translating findings into clear recommendations for Sales and GTM leadership.

Role Description We are seeking a senior, client-facing data leader to serve as a strategic partner across data governance, analytics architecture, and governed data product definition. This role acts as a critical bridge between client business stakeholders and a hybrid client/engineering delivery team, ensuring that decisions remain aligned to a clear, cohesive data governance and analytics strategy. This leader will help define how the governance program operates, author and socialize architecture and process standards, translate business priorities into structured data and reporting requirements, and guide engineering teams toward durable, scalable target-state solutions. The role is especially important in environments where governance rigor, reporting integrity, and analytics product clarity must be strengthened without requiring direct ownership of upstream data pipeline implementation. This is a capability-led leadership role requiring a strong combination of governance direction, architectural judgment, structured stakeholder management, and practical guidance for engineering and analytics teams. It is not a narrow specialist position, nor is it primarily an execution-only delivery management role. Qualifications - Significant experience leading data governance, data architecture, analytics architecture, or governed data product work in client-facing environments. - Strong executive stakeholder management experience, including the ability to work directly with business leaders, steering committees, and senior cross-functional stakeholders. - Experience translating business needs into structured target-state requirements for engineering teams. - Strong understanding of: - Data governance operating models - Metadata and data catalog approaches - Medallion architecture concepts - Semantic and reporting integrity considerations - KPI and analytics product design - Experience authoring standards, frameworks, methodology documents, and reusable delivery artifacts. - Ability to lead across architecture, engineering, and business conversations without needing to own every hands-on implementation detail. Requirements - Act as the primary liaison between senior client-side business leaders, including executive sponsors and C-suite stakeholders, and a hybrid client/engineering delivery team. - Facilitate structured decision-making, feedback loops, and alignment forums that connect business priorities to delivery realities. - Translate ambiguous or evolving strategic objectives into clear governance, architecture, and analytics workstreams. - Set the direction for operating the Data Governance program through ongoing advisory, process authorship, and operating-model refinement. - Connect engineering and business teams around a shared data governance strategy and target-state roadmap, informed by structured feedback from client counterparts and executive stakeholders. - Drive governance clarity across metadata, standards, business definitions, and downstream reporting integrity. - Partner with client leadership to evolve governance practices using Microsoft Purview on Azure. - Author gold-table specification documents that define target-state outputs for ETL pipelines within a medallion architecture. - Translate KPI, reporting, drill-down, and business decision needs into structured, engineering-ready specifications. - Guide architecture and semantic decisions that improve trust, reuse, and downstream analytical consistency. - Lead portfolio rationalization as an explicit sprint activity using a defined retain/refactor/retire methodology. - Continuously refine the methodology, validate criteria with client leadership, and identify the right business stakeholders for each rationalization decision. - Review and contribute to analytics product definition and delivery planning, including use cases such as Scheduling Optimization. - Shape KPI definitions, phased roadmaps, drill-down structures, and supporting architecture decisions. - Author and socialize data architecture standards that protect data quality and reporting integrity. - Provide day-to-day leadership, coaching, and structured guidance to practitioners working across engineering, architecture, and analytics-adjacent delivery. - Improve delivery quality by raising standards for documentation, design clarity, stakeholder communication, and cross-functional handoff quality. - Define terminology, reference architectures, and maturity models that differentiate Valtech in Data & AI. Benefits - This is a full-time position based in Canada. The offered salary range is $150,000-$200,000 annually, depending on experience and location. - A comprehensive insurance plan, where you can choose the module that best suits your needs—Gold, Silver, or Bronze. The employer may contribute up to 80% of your coverage depending on the selected module. This plan includes short- and long-term disability coverage. - Dialogue via Sun Life provides virtual healthcare services, allowing you to consult with a healthcare professional for emergencies, prescription renewals, and more. - A $500 Personal Spending Account, which can be used for healthcare reimbursements, gym memberships, public transit passes, office supplies, or contributions to your RRSP through Valtech. - A retirement plan where Valtech will match 100% of your RRSP contributions through a Deferred Profit Sharing Plan (DPSP), up to a maximum of 4%. - Access to a flexible vacation under Valtech's policy to support your work-life balance, with 5 days available during your probation period and a prorated amount calculated for the remainder of the year. - Personal Technology Reimbursement – $30/month for every employee-offered on day 1. - We close during the winter holidays and offer flexible scheduling throughout the year.

• Lead client-facing discovery sessions to elicit, document, and prioritize business requirements with operators, analysts, and executives • Translate ambiguous business problems into structured analytical work: data models, dashboards, KPI frameworks, and decision-support tools that get adopted • Write production-quality SQL against Snowflake, Databricks, BigQuery, or Redshift, and build trusted models in dbt or the client's modeling layer • Build and maintain dashboards and reporting in Looker, Tableau, Power BI, Sigma, or the tool the client lives in • Drive proactive analysis: surface trends, anomalies, and opportunities the client did not ask about but needs to see • Apply AI tooling (LLM-based analysis, natural language to SQL, agentic data exploration, AI-assisted documentation) to compress timelines and raise the quality bar on every deliverable • Set the cadence for client communication: status updates, demos, working sessions, and stakeholder reviews • Mentor junior analysts on the engagement and contribute to BOD's analytics playbooks, templates, and internal tooling