Lead Data Engineer
Toronto, Canada (onsite 5days)
Contract Role 1 is best described as a Lead Data Engineer responsible for building and operating scalable, high-quality data pipelines. It is more execution-focused with emphasis on engineering excellence, ETL/ELT, data quality, and operational reliability. Job Summary: Role: - Lead the development and maintenance of scalable, reliable data pipelines and data processing frameworks supporting a variety of business and product use cases. - Ensure data quality, integrity, and readiness by establishing and maintaining standards, validation processes, and monitoring frameworks. - Collaborate with cross-functional teams (Data Science, Product, Analytics, Infrastructure, and Engineering) to deliver end-to-end data solutions. - Identify and implement ETL/ELT processes, focusing on code robustness, automation, efficiency, and operational excellence. - Integrate emerging technologies to enhance data engineering capabilities and support evolving business needs. - Ensure timely, high-quality delivery while balancing multiple priorities. - Act as a subject matter expert on data modeling, pipeline optimization, large-scale data processing, and best practices. - Ensure compliance with internal policies and external data regulations, promoting secure and responsible data usage across the team. All About You - Extensive experience as a Data Engineer or in a similar role, with deep expertise in data engineering principles, data modeling, and pipeline development. - Experience working with big data and distributed systems (e.g. Spark, Hadoop, cloud-native big data services). - Strong working experience in Databricks, Hadoop-pySpark and related tools and technologies like, Apache Airflow, NiFi along with open formats like Delta and Iceberg - Strong SQL knowledge translating into analytical skills required for data analysis and defect management process - Strong understanding of data quality frameworks, validation methods, and monitoring tools - Familiarity with Agile methodologies and modern DevOps practices for data engineering - Working with CI/CD pipelines and modern source control practices - Strong communication skills - both verbal and written and strong relationship, collaboration skills and organizational skills - Ability to be high-energy, detail-oriented, proactive and able to function under pressure in an independent environment along with a high degree of initiative and self-motivation to drive results - Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement - Flexibility to work as a member of a matrix based diverse and geographically distributed project teams