Lead Data Engineer / Data Platform Lead

Lead Data Engineer / Data Platform Lead 121 Bloor st E, Toronto, Canada (onsite 5days) Role 2 is a more senior and strategic Lead Data Engineer / Data Platform Lead role. 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. All About You Technical 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. • Strong 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).

The role involves hands-on engineering as well as technical leadership, focusing on enterprise architecture and analytics enablement. It also requires stakeholder management and innovation for long-term platform strategy.

Candidates should have strong proficiency in Python and experience with Hadoop-based platforms, SQL, and data integration tools. A minimum of 8 years in data engineering with at least 2 years in a leadership role is required.

Identified from the job description. Confirm important requirements above.

• Python
• Pandas
• NumPy
• PySpark
• Impala
• Hadoop
• SQL
• ETL
• ELT
• Apache Airflow
• Apache NiFi
• Azure Data Factory
• Machine Learning
• Cloud Platforms
• CI/CD
• GenAI

• Technology
• Data & Analytics
• Software
• Engineering
• Consulting

Minimum experience

10+ years

Apply by

Aug 12, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available