The Technical Lead – AI & Analytics will lead a team of Data Scientists and Data Engineers responsible for building and delivering scalable machine learning solutions, data platforms, and analytics products using Microsoft Azure and Microsoft Fabric. This position combines hands-on technical leadership with team management, requiring strong expertise in machine learning architecture, data engineering, and enterprise analytics, along with the ability to drive accountability, mentor team members, and effectively manage stakeholder expectations.
Key Responsibilities
- Lead, mentor, and develop Data Scientists and Data Engineers while establishing clear expectations, priorities, and delivery timelines.
- Oversee assignments, track project milestones, ensure quality deliverables, and provide timely, constructive feedback to team members.
- Partner with technical and business stakeholders to communicate project status, risks, dependencies, and technical trade-offs.
- Lead the complete machine learning lifecycle, including feature engineering, model development, training, validation, deployment, and ongoing performance monitoring.
- Provide technical direction on machine learning algorithms, model architecture, hyperparameter optimization, and evaluation methodologies.
- Guide the development of predictive analytics solutions using project management and enterprise business data.
- Design and implement scalable, reliable data pipelines using Databricks, Apache Airflow, Fabric Data Factory, and Microsoft Fabric.
- Lead data architecture, modeling, and warehousing initiatives using Medallion Architecture and Fabric Lakehouse.
- Define and enforce engineering standards for ETL/ELT development, coding practices, source control, CI/CD, security, and data governance.
- Implement appropriate row-level and object-level security controls across enterprise data and analytics environments.
- Participate in and facilitate Agile ceremonies, sprint planning, estimation, backlog refinement, and technical discussions.
- Maintain accurate technical documentation, architectural standards, and project artifacts.
- Research emerging AI, machine learning, and data engineering technologies and recommend solutions that improve team capabilities and delivery efficiency.
- Support recruiting activities, technical interviews, onboarding, and development of new team members.
Required Qualifications
- Data Engineering: Strong expertise in ETL/ELT, data warehousing, data modeling, Medallion Architecture, data pipelines, and orchestration technologies. Experience leading enterprise-scale data engineering initiatives and teams.
- Machine Learning & Data Science: Working knowledge of ML architecture and model development, including supervised and unsupervised learning, deep learning, NLP, and time-series forecasting. Experience partnering closely with Data Science teams.
- Technical Leadership: Demonstrated ability to lead technical teams, establish expectations, manage workloads, track deliverables, provide feedback, and maintain accountability for results.
- Stakeholder Management: Strong ability to communicate technical concepts, project status, risks, and recommendations to both technical and business stakeholders.
- Problem Solving: Strong analytical and troubleshooting skills with the ability to decompose complex technical challenges and develop practical, scalable solutions.
- Collaboration & Communication: Excellent communication skills with the ability to work effectively across engineering, data science, product, and business teams.
- Agile Delivery: Experience working within Agile development environments, including sprint planning, estimation, ceremonies, and iterative delivery.