Data Platform Lead - Strategic Analytics & AI

Princeton IT Services, Inc; Toronto; Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Princeton IT Services, Inc. in Toronto is seeking a Lead Data Engineer / Data Platform Lead to shape strategy and deliver scalable data platforms.

This role blends hands-on engineering with technical leadership, enterprise architecture, and analytics enablement. You'll drive ingestion, transformation, and unification of large datasets across cloud and on-premises, collaborate with product, data science, and platform teams, and mentor engineers.

Qualifications

• 8+ years of experience in data engineering, big data analytics, or enterprise data platforms.
• Experience in leading or mentoring data engineering teams.
• Strong proficiency in Python and SQL with hands-on data engineering experience.
• Experience with cloud data platforms (Azure/AWS) and data lake architectures.
• Familiarity with GenAI/LLM-enabled data solutions is preferred.

Responsibilities

• Ingest, transform, aggregate, and process large-scale datasets for analytics.
• Design and maintain scalable data pipelines across Hadoop/Databricks and enterprise platforms.
• Drive data unification across multiple data sources into governed foundations.
• Partner with PMs, Data Science, Platform Strategy, and Tech teams to translate needs into engineering solutions.
• Provide technical leadership and mentorship to engineers; promote data governance and quality.

Skills

Python (Pandas, NumPy, PySpark)

SQL

Hadoop

Databricks

Airflow/NiFi

CI/CD for data pipelines

GenAI/LLM skills

Cloud platforms (Azure/AWS)

Data modeling

Data governance

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Databricks

Hadoop

Azure Data Factory

Job description

Princeton IT Services, Inc. in Toronto is seeking a Lead Data Engineer / Data Platform Lead to shape strategy and deliver scalable data platforms.

This role blends hands-on engineering with technical leadership, enterprise architecture, and analytics enablement. You'll drive ingestion, transformation, and unification of large datasets across cloud and on-premises, collaborate with product, data science, and platform teams, and mentor engineers.