senior data engineer.

We are seeking a highly accomplished and innovative Senior Data Engineer for an enterprise-level contract opportunity. In this role, you will join a rapidly growing, highly skilled analytics stream focused on delivering a premier interconnected digital and retail experience. You will take on a key technical capacity to design, construct, and scale robust data architectures that organize and optimize billions of rows of data for downstream analytics and enterprise decision-making.

As a senior data leader, you will bridge the gap between massive backend big data platforms and strategic business intelligence. Operating within a hybrid work model, you will translate complex business workflows into high-performance transformations, establish automated data pipelines, and build clean, reliable tables and views to power interactive dashboards. This role is ideal for an innovator who goes beyond routine reporting to engage in creative, hands-on optimization across large-scale cloud datasets.

Location: North York, ON (Hybrid work model with minimal office visits)

Contract Duration: 9 months (with long-term contract potential)

Advantages

Massive Data Scale: Design pipelines and optimize query frameworks processing billions of rows of transactional data.

Modern GCP Stack: Deepen your technical footprint utilizing Google BigQuery, GCP Dataflow, Airflow, Pub/Sub, and Vertex AI.

Hybrid Flexibility: Enjoy an excellent work-life balance through a hybrid model requiring minimal office visits.

Strategic Business Impact: Move beyond basic reporting by building data lake and warehouse models that directly shape short- and long-term organizational strategies.

Responsibilities
Pipeline Architecture: Design, develop, and maintain scalable data pipelines and robust Extract, Transform, Load (ETL) processes for both structured and unstructured datasets.

Dashboard Optimization: Build and optimize relational tables and views explicitly structured for enterprise dashboards and self-service analytics platforms.

Requirements Translation: Collaborate closely with business teams and data analysts to gather operational requirements and translate them into efficient data transformations.

Cross-Functional Collaboration: Partner with cross-functional business units, data scientists, and technology stakeholders to deploy reliable, unified data solutions.

Data Quality & Governance: Enforce strict data quality, governance frameworks, and operational performance tuning across large-scale data repositories.

Advanced Query Engineering: Leverage Google BigQuery, Python, and advanced storage procedures to build automated, highly optimized data solutions.

Process Automation: Streamline ingestion and transformation workflows, implementing automation strategies to maximize data integrity across user touchpoints.

Data Aggregation: Collect, aggregate, and prepare large-scale datasets to feed executive reporting tools, interactive dashboards, and operational scorecards.

Ad-Hoc Analysis Support: Provide clean data extractions and actionable insights to internal teams, responding promptly to critical ad-hoc analysis requests.

Continuous Improvement: Identify process efficiencies, resolve data bottlenecks, and proactively adopt modern data engineering tools, frameworks, and table formats.

Technical Articulation: Convey complex data structures and technical architecture adjustments clearly to business-oriented stakeholders, ensuring alignment with organizational goals.

Qualifications
Core Technical & Data Engineering Requirements
Professional Tenure: 7+ years of progressive, hands-on experience in data engineering, big data analytics, or a closely related quantitative field.

Cloud Platform Expertise: Extensive experience administering cloud data services, with a strong, dedicated focus on Google Cloud Platform (GCP) environments.

Advanced Languages & Tools: High proficiency in SQL and Python, paired with experience in one or more big data technologies (such as Google BigQuery, Redshift, or Snowflake).

ETL & Storage Mastery: Demonstrated success building and maintaining complex ETL/ELT pipelines, designing stored procedures, and optimizing complex queries for large-scale datasets.

Big Data Frameworks: Practical familiarity with advanced data processing frameworks and architectures, including Dataflow, Pub/Sub, PySpark, Airflow, and open table formats (such as Iceberg or StarRocks).

Applied AI Exposure: Hands-on exposure to machine learning platforms (such as Vertex AI) or applied AI/ML pipelines is highly preferred.

Domain & Source Familiarity: Solid understanding of operational workflows within the retail domain, along with beneficial familiarity handling clickstream data applications.

Education & Certifications
Education: Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related technical and quantitative discipline.

Technical Certifications: Relevant industry certifications are highly beneficial (e.g., Google Professional Data Engineer, AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate).

Operational Frameworks: Familiarity with structured IT frameworks, such as holding an ITIL Foundation asset designation.

Professional Soft Skills
Analytical Thinking: Superior problem-solving and critical thinking capabilities with a strong focus on process optimization, data profiling, and automation.

Communication & Influence: Excellent verbal and written communication skills, with a proven ability to explain complex technical concepts to non-technical business partners.

Execution & Adaptability: Outstanding organizational and time-management skills, with a track record of managing competing priorities and adapting quickly within fast-paced environments.

Summary
If you're interested in the Senior Data Engineer role based in North York, we encourage you to apply online at Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!

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 View email address on randstad.com to ensure their ability to fully participate in the interview process.

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