Job Title: Data Engineering Lead/ Data Platform Engineer Location: Toronto, Canada Experience: 7+ Years

About the Role We are looking for an experienced Data Engineering Lead to design, build, and optimize scalable data platforms that support advanced analytics, AI/ML, and business intelligence initiatives. The ideal candidate will have strong expertise in Python, PySpark, Hadoop, Databricks, SQL, and cloud-based data platforms, along with proven experience leading technical teams and delivering enterprise-scale data solutions. Key Responsibilities Data Engineering Lead the ingestion, transformation, aggregation, and processing of large-scale datasets for analytics and downstream applications. Design, develop, and maintain scalable, high-performance data pipelines using Hadoop, Databricks, and enterprise data platforms. Ensure data quality, reliability, scalability, performance, and availability across data engineering workflows. Integrate structured and semi-structured data sources into unified, governed data platforms. Build and optimize ETL/ELT pipelines using modern data integration tools. Advanced Analytics Enablement Process and analyze high-volume, high-velocity datasets using big data technologies and cloud-native platforms. Develop scalable data solutions that enable advanced analytics, reporting, and AI/ML initiatives. Generate actionable insights from transactional and product data to support business growth. Establish metrics and performance benchmarks to continuously improve data solutions. Cross-Functional Collaboration Partner with Product Managers, Data Scientists, Platform teams, and Engineering stakeholders to translate business requirements into scalable data solutions. Act as the technical liaison between business and engineering teams. Communicate architectural decisions, implementation strategies, and technical trade-offs effectively. Innovation Drive innovation by developing proof of concepts (POCs), prototypes, and pilot solutions. Evaluate and integrate new technologies, data sources, and modern engineering practices. Support continuous enhancement of enterprise data platforms and products. Technical Leadership Mentor and guide data engineers while promoting engineering best practices. Establish standards for data modeling, pipeline design, governance, performance optimization, and maintainability. Drive architectural consistency and long-term platform sustainability. Lead technical discussions, code reviews, and solution design sessions. Required Skills & Experience Technical Skills 7+ years of experience in Data Engineering, Big Data, or Enterprise Data Platforms. 2+ years of experience in a technical lead or leadership role is preferred. Strong programming skills in Python, including Pandas, NumPy, and PySpark. Hands-on experience with Hadoop ecosystem and Impala. Strong expertise in SQL and working with relational as well as distributed data stores. Experience with Databricks, Snowflake, and cloud platforms (Azure and/or AWS). Experience building ETL/ELT pipelines using Apache Airflow, Apache NiFi, or Azure Data Factory. Strong knowledge of data modeling, data warehousing, and large-scale data processing. Experience implementing CI/CD pipelines and DevOps practices for data engineering. Preferred Skills Experience supporting GenAI/LLM applications through scalable data pipelines. Knowledge of processing unstructured and semi-structured data (documents, logs, text). Understanding of enterprise data governance, privacy, security, PII handling, and access controls. Familiarity with AI data workflow monitoring, data quality validation, reproducibility, and cloud cost optimization. Exposure to Machine Learning concepts, feature engineering, and model serving. Analytical & Business Skills Strong analytical and problem-solving abilities. Experience working with large, complex datasets and identifying data quality issues. Ability to translate business requirements into scalable technical solutions. Excellent communication and stakeholder management skills. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. Experience working in Agile environments. Experience delivering enterprise-scale data engineering solutions for global organizations.

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