DataBank

Director of AI & Data Analytics

DataBank$130K — $180K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science, Data Science, Engineering; Master's preferred
  • 10+ years in data wrangling, building pipelines, or developing AI/ML solutions with 3+ years in leadership roles
  • Proven experience in building scalable data platforms and deploying production-grade AI/ML solutions
  • Deep expertise in data modeling, particularly star schemas; familiarity with Ralph Kimball's principles is a plus
  • Experience with modern AI/ML frameworks like PyTorch, TensorFlow, and Hugging Face
  • 5+ years in cloud-native data technologies; Snowflake preferred for data warehousing
  • 5+ years in Enterprise BI Reporting; Sigma Computing preferred, with knowledge of Power BI/Tableau as alternatives

Responsibilities

  • Partner with business leaders to understand data challenges and deliver meaningful insights
  • Design data solutions for self-service analytics to empower users
  • Build relationships with cross-functional teams to inform strategic decision-making
  • Measure and report on business metrics related to operational efficiency and service quality
  • Mentor business analysts in other departments on reporting strategies
  • Define and execute a comprehensive AI and analytics roadmap
  • Champion the integration of AI into critical workflows and build production-ready ML pipelines
  • Optimize complex data structures and enhance data warehousing strategies

Benefits

  • Lead a high-impact AI and data analytics function
  • Collaborative, values-driven work culture
  • Competitive compensation package
  • 401(k) matching
  • Health and wellness benefits
  • Generous paid time off (PTO)
Full Job Description
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. Key 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 Qualifications: Must-Haves: • 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) What Makes This Role Interesting This isn't just 'build dashboards and call it analytics.' You'll be: • Designing the data foundation for one of the fastest-growing data center companies in the world, operating 65+ data centers across North America • Building AI capabilities that optimize real-world physical infrastructure (power, cooling, capacity planning) • Creating intelligence systems that make our customers' lives better and our operations more efficient • Working cross-functionally with smart people who actually care about using data well • Having the autonomy to fix technical debt while building new capabilities Translation: You get to solve hard technical problems, work with interesting data, and see real business impact from your work. Why Join? • Lead a high-impact AI and data analytics function at the intersection of cloud, edge, and infrastructure innovation • Collaborative, values-driven culture that prioritizes integrity, innovation, and operational excellence • Competitive compensation, 401(k) match, health and wellness benefits, and generous PTO To be considered for this position, all candidates must be U.S. citizens or hold valid Green Card and live in the U.S.. This requirement is due to DataBank's compliance with FedRAMP and FISMA regulations. No third-party recruiters.

About DataBank

DataBank is a leading provider of enterprise-class data center, cloud, and interconnection services. The company was founded in 2005 and has since grown to become one of the largest privately held data center providers in the US, with facilities in Dallas, Minneapolis, and Kansas City. DataBank's services include colocation, cloud hosting, managed services, and network connectivity, and the company serves a wide range of customers, including Fortune 500 companies, healthcare providers, and government agencies. DataBank is known for its high-quality facilities and customer service, and has received numerous awards for its performance and innovation.
Learn more about DataBank
Size
1,000 employees
Industry
Net Income
$10 million
Founded
2005
5 Year Trend
+20%
Revenue
$200 million

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