Technical Lead — Artificial Intelligence & Analytics (AIA) - ERP

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Department:

• Data Science & Data Engineering Leadership

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Location:

• Tampa, FL or Remote

Summary of Duties & Responsibilities

As a Technical Lead – AI & Analytics at BST Global, you will lead a team of data engineers, data scientists, and full stack 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 expertise in data engineering, with knowledge of machine learning and web development. Leadership responsibilities include holding staff accountable for deliverables, providing constructive feedback, monitoring work assignments, and managing stakeholder expectations.

This role leads the AI and analytics capabilities of BST Global’s ERP system. This requires gaining knowledge of BST Global’s proprietary model architecture, Microsoft Fabric, Power BI reporting, semantic models, and understanding database mirroring and real-time data analysis.

Essential Functions

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 technical and non-technical audiences
• Drive the end-to-end engineering lifecycle, including feature engineering, model architecture and design, training, validation, deployment, and monitoring
• Architect scalable, resilient data pipelines using Microsoft Fabric native orchestration tools and 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
• Assist with interviewing and onboarding new team members to ensure team sustainability

What We’re Looking For

• 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
• Knowledge and Understanding of Data Science: Exposure to ML model architecture and design, including supervised and unsupervised learning, deep learning, NLP, and time-series forecasting; prior experience working with data science teams desired
• 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 articulate ideas and collaborate across cross-functional teams

Skills & Competencies

• Programming
• Python (expert), T-SQL (advanced), Spark/PySpark (advanced)
• Data Engineering
• ETL/ELT pipelines (expert), data modeling (advanced), data warehousing (expert), Medallion Architecture
• ML & Data Science
• Knowledge and experience executing and monitoring machine learning models
• Platforms & Tools
• Microsoft Azure and Fabric, Lakehouse, OneLake, semantic models (advanced), Power BI reporting
• Cloud & Security
• Azure compute, storage databases and developer tools (advanced); row-level and object-level security; performance monitoring and optimization
• DevOps & Process
• Azure DevOps Git, CI/CD pipelines, RESTful APIs, agile/scrum, Microsoft Power BI

Desired Skills

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Cloud cost optimization strategies

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Cross-tenant data sharing and Microsoft Power BI/semantic model sharing in Microsoft Fabric

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Observability tooling and platform monitoring

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Knowledge of project management and financial concepts, including budgets, revenue, profit and earned value

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Certifications in Microsoft Azure, Python, Fabric or SQL desired

Education or Prior Work Experience

Bachelor’s degree in computer science, data science, statistics, mathematics or a related field; master’s degree preferred; 7+ years in data engineering and/or data science, with at least 3 years in a technical leadership role overseeing cross-functional data teams

Reports To

Director, Engineering

Number Supervised

10–15 (data scientists, data engineers and full stack engineers)

Travel

Up to 5%

Classification

Exempt

Work Environment & Physical Demands

This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.