Technical Lead AI&A (Data Science & Engineering)

About Us

BST Global is a leading provider of enterprise software solutions for architecture, engineering, and consulting (AEC) firms. With over 50 years of innovation, we deliver project management, financial, and business intelligence solutions that drive efficiency and profitability. Our dynamic work environment fosters creativity, growth, and a passion for empowering AEC firms worldwide.

Summary of 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. Prior experience leading Data Science teams and translating business problems into analytical solutions.
• 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 architecture

ML & 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, OneLake, Semantic Models (advanced)

Cloud & Security:

Azure compute, storage, databases & developer tools (advanced), Row-level and object-level security, Performance monitoring & optimization

DevOps & Process:

Azure DevOps Git, CI/CD pipelines, RESTful APIs, Agile/Scrum, Power BI

Desired 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 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: 5-20 (Data Scientist and Data Engineers)

Travel: Up to 5%

Classification: Exempt

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