Senior Data Enablement Engineer

Scotiabank•Dallas, TX

6d•Onsite

About The Position

The Senior Data Enablement Engineer is a senior technical enablement leader and strategic interface between enterprise data platforms and the teams that consume them. The role drives scalable adoption, effective utilization, and measurable value realization of enterprise data platforms, services, and capabilities across the organization. It is highly technical but is not primarily development focused. The position provides technical and functional leadership across complex data enablement initiatives, translating platform capabilities, architecture standards, governance requirements, and engineering practices into practical, scalable consumption patterns. It works across platform engineering, architecture, data governance, security, infrastructure, operations, and Line of Business teams to establish consistent approaches for onboarding and adoption. The role identifies systemic barriers, influences platform priorities, creates reusable standards and enablement models, and operates autonomously across complex initiatives while influencing stakeholders, mentoring other enablement resources, and shaping the Data Enablement function. The successful candidate will lead onboarding and enablement for complex enterprise data platform consumers; operationalize governance requirements; establish documentation, reference patterns, and self-service resources; resolve cross-functional issues; support functional validation and user acceptance; and measure adoption, customer experience, and value realization. The role is based in Dallas, Texas. Scotiabank describes its benefit programs as flexible and designed to support employees’ family, financial, physical, mental, and social health needs.

Requirements

Demonstrated experience leading data enablement, enterprise data platform adoption, data architecture, technical product ownership, data engineering, or large-scale data transformation initiatives.
Strong experience with modern enterprise data environments and cloud technologies such as Microsoft Azure, Databricks, Google Cloud, or comparable platforms.
Deep understanding of enterprise data architecture and modern data platform concepts, including ingestion, transformation, orchestration, storage, processing, analytics, and data consumption.
Strong practical understanding of data governance disciplines, including metadata, lineage, data quality, classification, ownership, access controls, and lifecycle management.
Demonstrated ability to translate complex platform, architecture, and governance concepts into actionable guidance and scalable consumption patterns.
Experience developing platform standards, reference patterns, decision frameworks, onboarding models, or enterprise technical documentation.
Experience leading complex technical discovery and requirements discussions involving multiple stakeholder groups.
Typically 7–10 years of relevant experience in roles such as Data Enablement Engineer, Data Platform Lead, Data Architect, Senior Data Engineer, Platform Enablement Lead, Technical Product Lead, or Data Platform Consultant.

Nice To Haves

Spanish fluency is considered an asset.

Responsibilities

Lead technical enablement and onboarding for complex or strategic consumers of enterprise data platforms.
Design and evolve scalable onboarding frameworks covering platform capabilities, access models, workspace and environment strategies, supported service patterns, governance requirements, and operational responsibilities.
Establish reusable onboarding patterns that reduce complexity, improve consistency, increase self-service, and accelerate time to value.
Lead discovery and intake for complex initiatives, translating business objectives and technical requirements into platform adoption strategies.
Coordinate dependencies across platform engineering, architecture, governance, security, infrastructure, operations, and Line of Business teams.
Partner with governance, architecture, security, privacy, risk, and platform teams to operationalize enterprise data requirements.
Translate requirements for metadata, lineage, data quality, classification, ownership, retention, and access into practical consumption and onboarding patterns.
Define and promote consistent platform usage, data ownership, documentation, naming, and lifecycle-management practices.
Establish and maintain enablement assets such as reference patterns, decision frameworks, onboarding playbooks, implementation guidance, operating models, FAQs, and troubleshooting resources.
Define documentation and knowledge standards and enable frequently requested guidance to become repeatable self-service.
Build and support communities of data champions, platform advocates, and subject-matter experts.
Lead resolution of complex cross-functional issues and facilitate discussions where requirements, ownership, responsibilities, or platform direction are ambiguous.
Develop recommendations and decision materials for complex platform or operating-model questions; surface systemic risks, dependencies, and organizational friction.
Lead cross-functional working groups or initiatives to improve the enterprise data consumption experience.
Serve as a senior escalation point for complex platform adoption, onboarding, and functional issues, routing issues toward sustainable resolution.
Lead functional validation and user acceptance activities for significant platform capabilities and changes.
Establish feedback mechanisms that identify patterns across consumers and partner with engineering teams to improve platform usability.
Establish measures for platform adoption, enablement effectiveness, onboarding maturity, customer experience, and utilization of recommended patterns.
Analyze adoption and operational trends to identify barriers, capability gaps, and opportunities for improvement.
Connect platform usage and enablement activities to measurable technology and business outcomes.
Identify ways to reduce onboarding effort, shorten time to value, improve self-service, and increase adoption of standardized capabilities.
Measure and refine enablement interventions based on real-world outcomes.
Develop executive-ready insights on adoption trends, customer experience, systemic barriers, and opportunities requiring leadership attention.
Capture successful implementations and convert them into reusable enterprise patterns.