Our client, is seeking an experienced, highly analytical Senior Data Engineer to join their rapidly growing Analytics team.

In this high-impact role, you will design, build, and optimize scalable data pipelines to organize, transform, and manage billions of rows of data for advanced analytics and strategic decision-making.

Leveraging Google Big

Query, Python, and deep domain expertise, you will translate complex business requirements into high-performance transformations, building clean tables and views for executive dashboards and self-service analytics.

Operating in an empowering, data-driven environment, you will collaborate closely with business leaders and cross-functional technology squads to build automated, reliable data solutions that power customer experience initiatives and drive business value.

Duration: 4-Month Contract (with high potential for extension) Advantages Massive Data Scale Scope: Direct the design and optimization of enterprise-grade pipelines organizing, transforming, and optimizing billions of rows of data.

Modern GCP Cloud Ecosystem: Work extensively with top-tier cloud data technologies, including Google Big

Query, GCP Dataflow, Pub/Sub, PySpark, Airflow, and Vertex AI.

High-Visibility Business Impact: Deliver analytics-ready tables and self-service data models that directly inform strategic business decisions and executive dashboards.

Empowering & Collaborative Environment: Join a highly skilled, creative analytics group focused on creative problem-solving and modern data engineering practices.

Responsibilities Pipeline Engineering & Architecture: Design, develop, and maintain robust, scalable data pipelines and automated ETL/ELT processes for large-scale structured and unstructured datasets.

Big

Query & Analytics Optimization: Leverage Google Big

Query, Python, GBQ stored procedures, and advanced query optimization to build reliable data assets, aggregated scorecards, and dashboard tables.

Requirements Translation: Collaborate with business teams, data analysts,



and cross-functional stakeholders to translate complex business needs into clear, efficient data transformations.

Data Quality & Governance: Implement automated data validation checks, monitoring, and governance frameworks to guarantee accuracy, performance, and data integrity across massive datasets.

Process Automation & Analytics Support: Automate manual data processes, prepare ad-hoc data extractions, and derive actionable insights from complex data streams (including clickstream data).

Technical Communication: Effectively articulate complex technical concepts and pipeline designs to business-oriented stakeholders, ensuring strategic alignment.

Qualifications Professional Experience: 7+ years of progressive experience in data engineering, big data platform management, or a closely related field. GCP & Big

Query Mastery: Hands-on experience working within the Google Cloud Platform (GCP) ecosystem, with deep expertise in Google Big

Query, Big

Query stored procedures, and GCP data services.

Programming & SQL Depth: Advanced proficiency in Python and expert-level SQL skills with a track record of optimizing complex queries and building stored procedures.

Big Data & Orchestration: Proven experience with big data frameworks, workflow orchestration, and data warehousing platforms (PySpark, Apache Airflow, GCP Dataflow, Pub/Sub, Snowflake, or Redshift).

Education: Bachelors degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related quantitative discipline.

Preferred Assets & Certifications Professional certifications such as Google Professional Data Engineer, AWS Certified Data Analytics / Big Data Specialty, or Microsoft Certified: Azure Data Engineer Associate.





Familiarity with advanced analytics tools and modern data lake formats (Vertex AI, Apache Iceberg, Star

Rocks, Applied AI/ML concepts).

Exposure to clickstream data processing and ITIL frameworks (ITIL Foundation).

Summary If you are a tech-savvy Senior Data Engineer who pairs 7+ years of enterprise data engineering experience with deep expertise in Google Big

Query, Python, GCP pipelines, and large-scale data modeling, this 4-month contract opportunity is an ideal next step.

Bring your pipeline precision, analytical problem-solving skills, and collaborative mindset to our client''s analytics team today! Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada.

As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees.

In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada''s workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle.

We ask that all job applications please identify any accommodation requirements by sending an email to to ensure their ability to fully participate in the interview process.

📌 Senior Data Engineer (Toronto)
🏢 randstad canada
📍 Toronto