Director, Data Engineering

About the role

We are seeking a Director of Data Engineering to lead the strategy, architecture, and delivery of a modern enterprise data platform.

Responsibilities

• Own and actively contribute to the enterprise data strategy and roadmap.
• Define and prioritize the data engineering backlog, balancing foundational work, new business needs, AI enablement, reporting, and technical debt reduction.
• Design and oversee key data models, pipelines, integration patterns, and analytics platforms that support AI, BI, operational reporting, and decision-making.
• Lead data engineering and reporting teams including full-time employees, contractors, and vendors.
• Stay close to the work by reviewing pipeline designs, resolving complex data issues, and guiding architecture and implementation decisions.
• Establish practical standards for data quality, lineage, documentation, observability, governance, and operational support.
• Drive the evolution of the company’s data environment beyond basic SQL Server patterns into modern capabilities such as:
  • cloud-based data platforms
  • data lakes / lakehouse architectures
  • streaming and near-real-time data pipelines
  • scalable ELT/ETL frameworks
  • governed semantic and analytics layers
• Partner with business stakeholders, application development teams, AI engineers, analysts, and leadership to ensure data platforms meet current and future needs.
• Evaluate and introduce appropriate new technologies, tools, and design patterns that improve scalability, maintainability, speed, governance, and cost efficiency.
• Oversee data integration across enterprise systems such as ERP, CRM, project platforms, contract repositories, ticketing systems, and internally developed applications.
• Collaborate with infrastructure, security, and application teams to ensure data solutions align with enterprise architecture, security controls, identity standards, and cloud strategy.
• Build strong operating rhythms around prioritization, delivery, quality review, issue resolution, and stakeholder communication.
• Mentor senior engineers and analysts while raising the technical maturity of the broader team.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field. Equivalent experience may be considered.
• 15+ years of progressive experience in data engineering, analytics engineering, data architecture, or enterprise data platform development.
• 5+ years of leadership experience managing technical data teams.
• Proven experience designing and delivering modern data pipelines and analytics platforms in a business environment with multiple stakeholders.
• Strong experience with SQL and relational data platforms, but also a demonstrated ability to move beyond legacy-only approaches into modern data architecture.
• Experience with cloud data platforms, data lakes, and scalable data pipeline design.
• Experience with streaming, event-driven, or near-real-time data integration patterns.
• Experience establishing standards for data quality, lineage, documentation, and governance.
• Strong understanding of how data platforms support BI, reporting, analytics, and AI use cases.
• Experience leading a mix of full-time employees, contractors, and/or vendor resources.
• Ability to work in the details while also setting strategic direction.

Preferred Qualifications

• Experience with Azure-based data services and modern cloud-native data patterns.
• Experience with lakehouse or data lake architectures.
• Experience with streaming technologies and message/event-based integration patterns.
• Experience supporting AI and machine learning use cases with well-structured, governed data.
• Experience with semantic models, dimensional modeling, and performance optimization for analytics.
• Experience in operationally complex or multi-entity environments.
• Experience modernizing legacy reporting/data stacks into more scalable enterprise platforms.

Technical Environment

The ideal candidate should be comfortable working across a modern enterprise data environment that may include:

• SQL Server and relational platforms
• Azure data services and cloud-native data tooling
• Data lakes / lakehouse patterns
• Streaming or event-driven data architectures
• ETL / ELT orchestration frameworks
• Data modeling for analytics and operational reporting
• Data quality, lineage, cataloging, and documentation
• Integration with ERP, CRM, project systems, contract repositories, and custom applications
• AI and BI data enablement

Leadership Profile

Successful candidates will bring:

• A player-coach leadership style
• Strong technical credibility
• Comfort reviewing design details and guiding implementation
• A modernization mindset
• Strong architecture judgment
• A practical approach to governance and standards
• The ability to bridge engineering, analytics, and business needs
• A bias toward measurable business outcomes, not just technical elegance

Compensation

$220,000 - $250,000 salary