Lead Data Engineer

Hirematic Talent Solutions is hiring on behalf of a confidential client for an experienced Lead Data Engineer to join a high-performing engineering team. This role is ideal for a hands-on data engineering professional with expertise in designing scalable data pipelines, big data processing, and modern cloud-based data platforms. The successful candidate will lead the development of reliable, high-quality data solutions while driving engineering best practices, operational excellence, and data quality across enterprise-scale platforms.

Location: Toronto, Ontario (Onsite – 5 days per week)
Compensation: CAD $55/hour
Job Type: Contract

Responsibilities
Lead the design, development, and maintenance of scalable, reliable, and high-performance data pipelines.
Build and optimize ETL/ELT frameworks supporting enterprise data platforms and business applications.
Ensure data quality, integrity, governance, and operational reliability through validation, monitoring, and automated testing.
Collaborate with Data Science, Analytics, Product, Infrastructure, and Engineering teams to deliver end-to-end data solutions.
Design and implement efficient data models for large-scale analytical and operational workloads.
Optimize distributed data processing workloads using modern big data technologies.
Drive automation, CI/CD adoption, and engineering best practices across data platforms.
Evaluate and implement emerging technologies to improve scalability, performance, and operational efficiency.
Ensure compliance with enterprise data governance, security, and regulatory requirements.
Support production environments through monitoring, troubleshooting, and continuous improvement initiatives.

Qualifications
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline (or equivalent practical experience).
Extensive professional experience as a Data Engineer or Lead Data Engineer.
Strong expertise in data engineering principles, data modeling, and large-scale data pipeline development.
Experience working with distributed data processing frameworks and cloud-native data platforms.
Strong analytical, communication, collaboration, and problem-solving skills.
Ability to work independently in fast-paced, Agile environments.

Required Skills
Databricks
Apache Spark
PySpark
Hadoop
SQL
Data Engineering
ETL / ELT
Data Modeling
Apache Airflow
Apache NiFi
Delta Lake
Apache Iceberg
CI/CD
Data Quality
Data Validation
Big Data
Distributed Systems
Agile
DevOps

Preferred Skills
Cloud-native data platforms.
Proof-of-Concept (PoC) development.
Performance tuning and pipeline optimization.
Source control and Git workflows.
Enterprise-scale data platform experience.
Experience working with geographically distributed engineering teams.

Ideal Candidate
Strong hands-on data engineer with leadership capabilities.
Passionate about building scalable and reliable data platforms.
Comfortable owning complex engineering initiatives from design through deployment.
Strong collaborator who enjoys solving large-scale data engineering challenges.
Continuously explores emerging technologies and modern engineering practices.