Director, Data Engineering & Architecture

Haag, a Salas O'Brien Company•,

6d•$175,000 - $200,000•Remote

About The Position

Salas O’Brien is building a next-generation Data & AI organization designed to transform how data is managed, governed, and leveraged across the enterprise. The Director of Data Engineering & Architecture is responsible for establishing and leading the enterprise data foundation that powers analytics, reporting, artificial intelligence, automation, and future digital innovation initiatives. This role owns the enterprise data architecture strategy, data engineering function, information architecture framework, master data management capabilities, and technical implementation of data governance controls. The Director will build and lead a team of Data Engineers, Data & Information Architects, and Governance professionals while partnering closely with business leaders, Information Technology, Finance, Human Resources, Operations, and the broader Digital & AI organization. Salas O’Brien has grown significantly through acquisition, resulting in a diverse technology landscape and multiple sources of enterprise data. This role will lead the effort to integrate those systems into a scalable, secure, and trusted data ecosystem that enables enterprise reporting, AI solutions, operational decision-making, and future growth. The ideal candidate combines deep technical expertise with strategic leadership capabilities and thrives in environments where building, influencing, and delivering results are equally important.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related discipline.
12+ years of progressive experience in data engineering, data architecture, or enterprise data management.
5+ years of leadership experience managing technical teams and enterprise-scale initiatives.
Demonstrated success designing and implementing modern enterprise data platforms.
Experience integrating multiple enterprise systems and data sources within complex organizations.
Strong understanding of: Data architecture, Data engineering, Master data management, Information architecture, Data governance, Data quality management
Experience building enterprise reporting, analytics, and data product capabilities.
Strong business acumen and ability to align technical investments with organizational objectives.
Exceptional communication, collaboration, and stakeholder management skills.
Authorization to work in the United States without sponsorship.

Nice To Haves

Experience within professional services, engineering, consulting, construction, or acquisition-driven organizations.
Experience leading data transformation initiatives in organizations with multiple operating companies or business units.
Hands-on familiarity with Databricks, Delta Lake, Unity Catalog, Azure Data Services, Microsoft Fabric, or comparable platforms.
Familiarity with graph databases and relationship-based data architectures.
Experience supporting AI, machine learning, automation, and advanced analytics initiatives.
Knowledge of compliance frameworks such as NIST, SOC 2, CMMC, GDPR, HIPAA, or similar standards.
Experience developing enterprise data products and self-service analytics capabilities.
Master’s degree in a related field.

Responsibilities

Define and execute the enterprise data engineering strategy supporting business growth, operational excellence, analytics, and AI initiatives.
Establish enterprise standards for data ingestion, integration, transformation, storage, quality, and delivery.
Develop a scalable data architecture capable of supporting a rapidly growing and acquisition-driven organization.
Create and maintain a multi-year roadmap for enterprise data capabilities and platform investments.
Ensure data architecture decisions align with broader Digital & AI, IT, and business strategies.
Lead the design, implementation, and operation of the company’s enterprise data platform and lakehouse architecture.
Establish scalable patterns for batch, real-time, and event-driven data integration.
Oversee enterprise data storage, metadata management, lineage, access management, and audit capabilities.
Define architectural standards that promote reliability, performance, scalability, and maintainability.
Evaluate and recommend emerging technologies that enhance the company’s data capabilities.
Establish and maintain enterprise data domains, business entities, and authoritative sources of truth.
Lead development of enterprise information architecture frameworks that support analytics, reporting, and AI solutions.
Oversee master data management strategies for critical business entities, including clients, projects, employees, vendors, and financial data.
Ensure consistency of data definitions, business rules, and enterprise reporting standards.
Partner with Data & Information Architects to maintain enterprise data models and architecture standards.
Develop repeatable integration frameworks for newly acquired firms and business units.
Assess data quality, system architecture, and integration complexity during acquisition activities.
Create data onboarding playbooks that accelerate integration timelines while maintaining quality and governance standards.
Partner with business leaders to prioritize enterprise integration efforts based on strategic value and business impact.
Drive consolidation of fragmented systems and data assets into enterprise platforms where appropriate.
Partner with the Director of Data & AI Governance to operationalize governance controls within enterprise platforms and workflows.
Ensure technical implementation of classification, retention, lineage, stewardship, and access management requirements.
Establish data quality frameworks, monitoring capabilities, and remediation processes.
Support audit readiness and compliance requirements through robust technical controls and documentation.
Promote enterprise accountability for data ownership and stewardship.
Recruit, develop, and lead a high-performing team of Data Engineers, Data & Information Architects, and Governance professionals.
Establish clear performance expectations, development plans, and career pathways.
Foster a culture of collaboration, innovation, accountability, and continuous improvement.
Mentor team members and encourage adoption of best practices across the organization.
Build organizational capability through knowledge sharing, training, and partnership.
Serve as a trusted advisor to executive leadership on enterprise data strategy and capabilities.
Partner with Finance, Operations, Human Resources, Technology, and Business Unit leaders to understand priorities and align solutions.
Collaborate closely with AI, Automation, and Analytics leaders to ensure data platforms support future use cases.
Communicate technical concepts effectively to both technical and non-technical audiences.
Translate business objectives into scalable data solutions that deliver measurable value.