Job Title: Lead Data Engineer / Data Platform LeadLocation: Toronto, Canada (onsite 5days)Summary: Thisis a more senior and strategic Lead Data Engineer / Data Platform Leadrole. In addition to hands-on engineering, it emphasizes technical leadership, enterprise architecture, analytics enablement, stakeholder management, innovation, and long-term platform strategy. It also introduces preferred experience in GenAI/LLM-enabled data platforms, making it broader in scope than the first role.Job Summary:Data Engineering Lead- Lead the ingestion, transformation, aggregation, and processing of large scale datasets to enable advanced analytics and downstream consumption.- Design, build, and maintain robust, scalable data pipelines across Hadoop/Databricks and enterprise data platforms, ensuring high standards of data quality, reliability, performance, and availability.- Drive data unification initiatives, integrating multiple structured and semi structured data sources into a cohesive, governed analytical foundation.Advanced Analytics Enablement- Manipulate and analyse high volume, high velocity, and high dimensional datasets using modern big data framework and/or Cloud native applications- Analyse large volumes of transactional and product data to produce insights and actionable recommendations that support business growth and value realisation.- Apply metrics, measurement frameworks, and benchmarking techniques to evaluate solution effectiveness and drive continuous improvement.Cross Functional Collaboration- Partner with Product Managers, Data Science, Platform Strategy, and Technology teams to understand analytical and data requirements and translate them into scalable engineering solutions.- Act as a technical bridge between business, analytical, and engineering teams, clearly articulating architecture decisions, trade offs,



and implementation approaches.- Enable alignment across stakeholders to ensure data solutions are directly tied to business and customer outcomes.Innovation & Value Creation- Identify innovation opportunities and deliver proofs of concept, prototypes, and pilot solutions aligned to near term and future business needs.- Integrate new and emerging data assets that enhance existing platforms, products, and services, strengthening overall value propositions.- Gather and synthesise feedback from clients, product, engineering, and sales teams to inform new solutions and product enhancements.Technical Leadership & Mentorship- Provide technical leadership, guidance, and mentorship to data engineers and analysts, setting standards for engineering quality, scalability, performance, and maintainability.- Promote best practices in data modelling, pipeline design, performance optimisation, and data governance.- Influence engineering standards, architectural consistency, and long term platform sustainability.___All About YouTechnical Skills & Experience- Strong proficiency in Python, including Pandas, NumPy, PySpark, with hands on experience using Impala.- Proven experience working on Hadoop based platforms, performing large scale data extraction, transformation, and processing.- Strong SQL skills and experience working with both relational and distributed data stores.- Experience with enterprise data platforms and business intelligence ecosystems.- Hands on experience with ETL / ELT and data integration tools, such as Apache Airflow, Apache NiFi, Azure Data Factory.- Experience in data modelling, querying, data mining,



and reporting over large volumes of granular data.- Exposure to machine learning concepts and analytical techniques used in advanced data solutions and Feature calculations and Model serving is a big plus.- 8+ years of experience in data engineering, big data analytics, or enterprise data platforms, including 2+ years in a lead or technical leadership role.- Experience working with cloud based data platforms (Azure/AWS, Databricks/Snowflake), including data lakes, distributed compute, and storage services.- Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows.- GenAI / LLM Skills (Preferred)- Experience enabling GenAI/AI products through scalable, reliable data ingestion and transformation pipelines (batch and streaming).- Exposure to unstructured and semi-structured data processing (documents/logs/text) and building curated datasets for downstream consumption.- Solid understanding of data governance, privacy, and security requirements when using enterprise data with AI (PII handling, access control, auditability).- Familiarity with operationalizing AI data workflows (monitoring, data quality checks, reproducibility, and cost-aware scaling in cloud environments).Analytical & Business Acumen- Strong experience collecting, standardising, and summarising diverse datasets while identifying patterns, inconsistencies, and data quality issues.- Solid understanding of how analytics, metrics, and visualisation support business decision making.- Ability to comprehend complex operational systems and deliver scalable analytics and information products to a global user base.Ways of Working- Comfortable operating in a fast paced, delivery driven environment, both as a hands on contributor and a technical leader.- Ability to move seamlessly between business, analytical, and technical contexts, communicating clearly with diverse audiences#J-18808-Ljbffr

📌 Lead Data Engineer / Data Platform Lead (Toronto)
🏢 Princeton IT Services
📍 Toronto