Director of AI & Data Analytics

About the role

We're looking for a hands-on Director of AI & Data Analytics who still loves getting their hands dirty in code. This isn't a "pure management" role where you sit in meetings all day – You’ll spend roughly 50% of your time leading and mentoring your team and other engineering members, and the remaining 50% hands-on, writing SQL, building data pipelines, architecting solutions, and tackling complex technical challenges directly. You'll be the technical architect and strategic driver of DataBank's data and AI initiatives, turning our mountain of infrastructure, operations, and customer data into actual intelligence that people use.

Responsibilities

• Be the Data Whisperer: Building Business Intelligence & Insights
  • Partner with leaders across the business to understand their data challenges (and translate "I need a report" into "here's the insight you actually need")
  • Design and model data solutions that enable self-service analytics – because teaching people to fish is way better than becoming the company's fish-delivery service
  • Build cross-functional relationships with engineering, product, finance, operations, and marketing teams who all have "just one quick data question"
  • Measure and report key business metrics, operational efficiency, customer growth, and service quality
  • Mentor and align business analysts in other departments on their reporting strategies
• AI & Analytics Strategy
  • Define and execute a company-wide AI and analytics roadmap aligned with DataBank’s business and technology objectives
  • Drive the evolution from traditional BI to predictive and generative AI-driven insights across DataBank’s data ecosystem
  • Champion the integration of AI into key workflows, from customer intelligence to operational automation
  • Develop AI models for forecasting, anomaly detection, and intelligent automation in data center operations
  • Build ML pipelines that go beyond PowerPoints demos and into production
• Fix What's Broken, Build What's Missing
  • Untangle and optimize data structures that have gotten "organically complex" over time
  • Optimize the existing MSSQL to Snowflake replication and data warehousing strategy to establish patterns of anti-fragility
• Lead (When You're Not Coding)
  • Build and mentor a high-performing team of data engineers, scientists, and AI specialists
  • Define and execute an AI and analytics roadmap that aligns with business objectives (the real ones, not just buzzword bingo)
  • Champion the evolution from "here's what happened" to "here's what's about to happen and what we should do about it"
• Make Data Governance Not Boring
  • Implement data quality, security, and compliance frameworks that meet regulatory standards
  • Ensure AI practices align with compliance requirements where applicable

Qualifications

• Bachelor’s degree in computer science, Data Science, Engineering, or related field (Master’s preferred)
• 10+ years wrangling data, building pipelines, or developing AI/ML solutions with 3+ years in leadership roles
• Proven experience building scalable data platforms and deploying production-grade AI/ML solutions
• Deep expertise in data modeling – you dream in star schemas and know when to denormalize
• Proven track record building scalable data platforms and deploying production-grade AI/ML solutions
• Experience with modern AI/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain)
• Deep Expertise in cloud-native data technologies, you've built data transformations with:
• Data warehousing - 5 years. Snowflake preferred, Databricks, AWS/Azure data services are an acceptable alternative
• Enterprise BI Reporting - 5 years. Sigma Computing preferred. Power BI or Tableau is an acceptable alternative
• Orchestration tools (Airflow and dbt)