Senior AI & Azure Data Engineering Technical Lead

AI & Azure Data Engineering Technical Lead

Data Science & Data Engineering Leadership | Fabric

Location: Remote USA

Type: Full time/Direct

*** Our client does not now or in the future provide any form of sponsorship. Applicants must be eligibe to work direct without any sponsorship required. U.S Citizen, Green Card/EAD***

Remote Core Hours: 9:00 AM – 6:00 PM EST

This is a full-time, remote position leading a team of Data Scientists and Azure Data Engineers in the design, development, and delivery of machine learning models, enterprise data pipelines, and analytics solutions on Microsoft Azure and Fabric.

• This full-time remote role is for a Lead Azure Data Engineer/Architect responsible for designing, building, and optimizing data solutions on Microsoft Azure.
• he Lead Azure Data Engineer/Architect will collaborate closely with stakeholders to gather requirements, translate them into technical designs, and ensure data quality, security, and governance standards are met.
• Day-to-day responsibilities include hands-on development, performance tuning, code reviews, and mentoring other data engineers.

Prior experience leading Data Science teams and translating business problems into analytical solutions.

Data Platform & Engineering Expertise

• Architect and build scalable pipelines using:
• Databricks
• Apache Airflow
• Fabric Data Factory
• Azure Date Engineering
• Microsoft Fabric (Lakehouse, OneLake, Semantic Models)
• Implement medallion architecture and modern data warehousing
• Ensure scalability, performance, and resilience
• Own full lifecycle: feature engineering → model design → training → validation → deployment → monitoring
• Drive model selection, tuning, and evaluation strategies
• Deliver predictive analytics tied to project and financial data

REQUIRED SKILLS

Technical (Hands-On Leadership Required)

• Expert in Python, advanced T-SQL, strong Spark/PySpark
• Deep experience in:
• ML model architecture (required) – supervised, unsupervised, NLP, time-series
• ML deployment in production (required) – end-to-end lifecycle ownership
• Azure Data Factory (ADF) for ML pipelines (required)
• Data engineering – ETL/ELT, data warehousing, medallion architecture
• Advanced experience with:
• Azure ecosystem
• Databricks
• Microsoft Fabric
• Apache Airflow

Experience

• 7+ years in Data Engineering, Data Science, or Machine Learning Engineering
• 3+ years in technical leadership roles
• Bachelor’s degree required (Master’s preferred)