Director of Data Engineering

LHH is seeking an experienced and strategic Director of Data Engineering to lead two mission-critical functions: the Core Data Engineering team and the 360 B2B marketing data platform. This role involves providing strategic leadership, hands-on technical contributions, and driving the roadmap for data products and pipelines that enhance decision-making and marketing intelligence.

Responsibilities:

• Drive measurable improvements in data availability, platform reliability, and time-to-insight across product and marketing use cases
• Own the vision and roadmap for Core Data Engineering and the 360 SaaS platform
• Act as technical lead and co-owner of the 360 product roadmap, working closely with Product Management to deliver value to studio clients
• Collaborate with Product, Data Science, and Business stakeholders to deliver scalable, compliant data products
• Drive innovation in clean room technology, marketing data activation, and advanced use of first-party data
• Lead, mentor, and scale a team of approximately 10-15 engineers
• Foster a high-performance, self-directed, and accountable culture focused on quality, velocity, and continuous improvement
• Partner with Privacy, Legal, and Data Governance teams to ensure ethical and compliant data use
• Architect solutions for data ingestion, orchestration, warehousing, and analytics using AWS-native services
• Oversee integrations with internal and external platforms including social, ad networks, and transactional systems
• Support deployment of ML models (e.g., recommendation systems, customer segmentation, forecasting) into production pipelines

Requirements:

• BS in Computer Science, Engineering, or related field (or equivalent practical experience)
• 10+ years in data engineering roles working with big data, ETL pipelines, and orchestration
• 5-7+ years leading technical teams (Data Engineering, Application Engineering, or Platform Engineering)
• Experience building data warehouses from the ground up, ideally with medallion/lakehouse architecture
• Operates with autonomy and takes ownership of ambiguous challenges without waiting for top-down direction
• Familiarity with machine learning pipelines and deploying ML models into production environments
• Strong knowledge of the Software Development Life Cycle (SDLC) and agile development practices
• Excellent communication, collaboration, and stakeholder management skills
• Experience managing multiple priorities and driving execution in fast-paced environments