Director Enterprise Data Mgmt & Analytics

Walter Surface Technologies Incorporated•Pointe-Claire, QC

13h

About The Position

Walter Surface Technologies’ Data & Analytics function is a strategic, enterprise-wide business unit, and this role leads that capability - delivering accurate, governed and actionable data to all employees for better decision making, while continuing to scale and modernize the estate. The Director, Enterprise Data Management and Analytics leads the development and maintenance of tools that permit the organization to make data-driven decisions. You own Data Management, Data Governance, Data Engineering, Data Integration and drive Data Insights across all Walter entities. Your portfolio spans Business Intelligence and self-service analytics on a modern Snowflake & Sigma Computing platform, enterprise integrations across a multi-ERP estate (D365 F&O, SAP, Oracle), the B2B commerce ecosystem (Salsify, Salesforce, Mulesoft), AI/ML & GenAI capabilities, and the direct administration, maintenance and support of the data stack, reusable data products and business logic that deliver the consolidated data model consumed by downstream systems such as Logility, Sigma and other enterprise applications. You bridge the gap between business and technical stakeholders, translating strategy into data roadmaps and communicating value, trade-offs and progress to senior leadership. Your track record spans data management, engineering leadership and enterprise technology, with a strong background in IT, sales and marketing, and the ability to build sound foundations across technology, people and process.

Requirements

High degree of resourcefulness, flexibility, and adaptability.
Leadership, staff management, and team building skills.
Strong negotiation and prioritization skills.
Strong interpersonal communication and relational skills; good organizational and project management skills; sound judgment; initiative; detail-oriented.
Strong analytical and logical problem-solving skills.
Ability to partner effectively with business functional groups (Finance, Marketing, Sales, Operations).
Experience in the distribution industry, with knowledge of supply chain and warehouse operations is an asset.
Prior experience with one or more ERP systems and related applications in a distribution / supply chain environment - multi-ERP estates (D365 F&O, SAP, Oracle) preferred.
Experience managing budgets, building business or investment cases, and applying FinOps discipline to cloud run-rate.
Deep knowledge of modern cloud data architecture - Snowflake, Databricks/Spark lakehouse, dbt/ELT pipelines, governed semantic layers, SQL and NoSQL databases - modern self-service analytics (Sigma Computing), plus practical data-system administration and support, including access, configuration, monitoring, troubleshooting, and the design and maintenance of consolidated data models, reusable data products and business logic for systems such as Logility, Sigma and others.
Experience delivering AI/ML and GenAI capabilities (RAG, LLM-powered search, vector databases) in an enterprise context.
Knowledge of Web and Mobile apps design/application principles and modern applications; product information management experience is a plus.
Experience with most data governance aspects and master data management.
Demonstrated experience analyzing business and technical requirements.
Strong analytical and customer service skills.
Highly effective project management and change management.
Ability to explain technical concepts and theories to non-technical audiences at all levels of the organization.
Solid experience delivering automated dashboards with key KPIs.
Degree in Computer Science, Data Science or equivalent experience; MBA preferred.
Minimum 10 years of experience in a data management role.

Nice To Haves

MBA preferred.
Knowledge of Web and Mobile apps design/application principles and modern applications; product information management experience is a plus.
Experience in the distribution industry, with knowledge of supply chain and warehouse operations is an asset.

Responsibilities

Own and evolve the enterprise data & analytics strategy, roadmap and data governance framework across all Walter Surface Technologies entities, providing both tactical and strategic leadership and managing 3rd-party vendors and consultants.
Lead the planning, development and management of Data initiatives, Business Intelligence, self-service analytics, web, intranet and product information services, programs and operations on a modern, governed Snowflake & Sigma Computing platform, including day-to-day administration, support and ongoing maintenance of the data stack, data products and business logic that power downstream operational and analytical systems.
Direct enterprise data engineering and integration across a multi-ERP estate (D365 F&O, SAP, Oracle) and the B2B commerce ecosystem (Salsify, Salesforce, Mulesoft), unifying analytics into a single governed source of truth.
Operate, administer, support and continuously maintain a modern data engineering stack - a segregated analytical data store, ELT pipelines, governed semantic layer, curated data products and embedded business logic - including monitoring jobs, resolving data issues, managing configurations and access, keeping reporting load off production ERPs, simplifying acquisition integrations and delivering a consolidated data model for downstream systems such as Logility, Sigma and others.
Embed scalable AI/ML and GenAI systems on modern data and cloud platforms (Databricks, Spark, Snowflake) - demand forecasting, product classification, and governed LLM-powered search and document intelligence - setting best practices for experimentation and validation against both technical and business outcomes.
Act as program / project manager and operational data-system owner for complex business systems transformations and acquisition integrations (BI / Data / Web / Mobile Apps) through reusable, scalable data products that preserve shared business definitions, support production use and feed enterprise downstream systems.
Institute enterprise data governance (master data, quality, lineage, stewardship) and FinOps discipline that makes data audit-ready and lowers cloud run-rate.
Develop data procedures and policies, working closely with departments to collect, prepare, organize, protect and analyze data assets; understand, manage and influence the collection, storage, pipelines, quality and protection of data.
Implement data privacy policies and ensure compliance with data protection regulations (GDPR, AODA/ADA).
Enable data value extraction - efficiencies and increased revenue based on insights derived from data - and effectively communicate the status, value and importance of data collection and governance to executives and staff.
Build and coach a high-performing, cross-border team of data science, engineering and analytics practitioners - owning hiring, mentorship and performance management - while creating a culture of data-driven decisions backed by investigation and collaboration.
Serve as a trusted partner to key business executives focused on the customer, enterprise risk management, regulatory compliance and finance; establish and oversee mechanisms to monitor compliance with governance and standards.