Director of AI & Data Analytics

Databank Holdings•Dallas, TX

72d

About The Position

DataBank Holdings Ltd. is a leading provider of enterprise-class data center, cloud, and interconnection services, offering customers 100% uptime availability of data, applications, and infrastructure. DataBank's managed data center services are anchored in world-class facilities. Our customized technology solutions are designed to help customers effectively manage risk, improve technology performance, and allow focus on core business objectives. DataBank is headquartered in the historic former Federal Reserve Bank Building, in downtown Dallas, TX. DataBank is proud to be an Equal Opportunity Employer. Our work culture does not discriminate based on actual or perceived race, creed, color, religion, alienage or national origin, ancestry, citizenship status, age, disability or handicap, sex, marital status, veterans' status, gender, gender identity, gender expression, genetic information, sexual orientation, or any other characteristic protected by applicable federal, state, or local law. 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. Think: predictive analytics that prevent problems before they happen, AI models that optimize efficiency across data centers, and self-service analytics that make everyone's life easier. The ideal candidate blends technical depth in data architecture, AI/ML engineering, and cloud analytics with a strong business sense for driving measurable outcomes.

Requirements

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. Extra credit if you have a small shrine dedicated to Ralph Kimball.
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)

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" teams to quantify ROI and inform strategic decision-making
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