Technical Lead AI&A (Data Science & Engineering)

Duties & Responsibilities: As a Technical Lead – AI & Analytics at BST Global, you will lead a team of Data Scientists and Data Engineers in the design, development, and delivery of machine learning models, data pipelines, and analytics products built on Microsoft Azure and Fabric technologies. This role requires deep expertise in ML model architecture and design, data engineering, and proven team leadership skills including holding staff accountable for deliverables, providing constructive feedback, monitoring work assignments, and managing stakeholder expectations.

What You’ll Do: Lead, mentor, and coach a cross-functional team of Data Scientists and Data Engineers; monitor work assignments, track milestones, and hold staff accountable for the quality and timeliness of deliverables Manage stakeholder expectations by proactively communicating progress, risks, and trade-offs to both technical and non-technical audiences Drive the end-to-end ML lifecycle including feature engineering, model architecture and design, training, validation, deployment, and monitoring Provide technical guidance on ML model selection, hyperparameter tuning, and evaluation metrics; oversee predictive analytics solutions for project management data Architect scalable, resilient data pipelines using Databricks, Apache Airflow, Fabric Data Factory, and Microsoft Fabric; lead data modeling and warehousing efforts leveraging medallion architecture and Fabric Lakehouse Establish and enforce engineering standards for ETL/ELT processes, code quality, version control, CI/CD, and security including row-level and object-level controls Participate in and lead Agile ceremonies; accurately estimate assignments and maintain technical documentation Evaluate emerging AI/ML frameworks and data engineering tools, making recommendations that advance team capabilities Assist with interviewing and onboarding new team members to ensure team sustainability

What We’re Looking For: Data Science & ML Expertise: Deep knowledge of ML model architecture and design, including supervised and unsupervised learning, deep learning, NLP, and time-series forecasting. Data Engineering Proficiency: Expert-level understanding of ETL/ELT pipelines, data warehousing, medallion architecture, and orchestration tools. Prior experience leading Data Engineering teams building enterprise-scale data platforms. Leadership & Accountability: Proven ability to set clear expectations, monitor deliverables, provide constructive feedback, and hold team members accountable. Skilled at managing stakeholder expectations across technical and business audiences. Problem-Solving & Communication: Strong analytical skills with the ability to break down complex problems and develop effective solutions. Effectively articulates ideas and collaborates across cross-functional teams.

Required Technical Skills: Programming: Python (expert), T-SQL (advanced), Spark/PySpark (advanced)Data Engineering: ETL/ELT pipelines (expert), Data modeling (advanced), Data warehousing (expert), Medallion architectureML & Data Science: ML model architecture & design (advanced), Model training, validation & deployment (advanced), Feature engineering Platforms & Tools: Databricks (advanced), Apache Airflow (advanced), Fabric Data Factory (required), Microsoft Fabric incl. Lakehouse, One Lake, Semantic Models (advanced)Cloud & Security: Azure compute, storage, databases & developer tools (advanced), Row-level and object-level security, Performance monitoring & optimization Dev Ops & Process: Azure Dev Ops Git, CI/CD pipelines, RESTful APIs, Agile/Scrum, Power BIDesired Skills Cloud cost optimization strategies Cross-tenant data sharing and Power BI/Semantic Model sharing in Microsoft Fabric Observability tooling and platform monitoring Knowledge of project management and financial concepts including budgets, revenue, profit, and earned value Certifications in Microsoft Azure, Python, SQL, or Databricks

Education & Experience: Bachelor’s degree in computer science, Data Science, Statistics, Mathematics, or a related field; Master’s degree preferred. 7+ years in data engineering with at least 3 years in a technical leadership role overseeing cross-functional data teams.

Reports To: Director, Engineering Number Supervised: 5-20 (Data Scientist and Data Engineers)

Travel: Up to 5%Classification: Exempt

Work Arrangement: Remote / Hybrid if local to Tampa, FL