Senior Data Engineer Job at Randstad (North York)

Job Description

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.

Job Responsibility

Design, develop, and maintain scalable data pipelines and robust ETL processes for both structured and unstructured datasets
Build and optimize relational tables and views explicitly structured for enterprise dashboards and self-service analytics platforms
Collaborate closely with business teams and data analysts to gather operational requirements and translate them into efficient data transformations
Partner with cross-functional business units, data scientists, and technology stakeholders to deploy reliable, unified data solutions
Enforce strict data quality, governance frameworks, and operational performance tuning across large-scale data repositories
Leverage Google BigQuery, Python, and advanced storage procedures to build automated, highly optimized data solutions
Streamline ingestion and transformation workflows, implementing automation strategies to maximize data integrity across user touchpoints
Collect, aggregate, and prepare large-scale datasets to feed executive reporting tools, interactive dashboards, and operational scorecards
Provide clean data extractions and actionable insights to internal teams, responding promptly to critical ad-hoc analysis requests
Identify process efficiencies, resolve data bottlenecks, and proactively adopt modern data engineering tools, frameworks, and table formats
Convey complex data structures and technical architecture adjustments clearly to business-oriented stakeholders, ensuring alignment with organizational goals

Requirements

7+ years of progressive, hands-on experience in data engineering, big data analytics, or a closely related quantitative field
Extensive experience administering cloud data services, with a strong, dedicated focus on Google Cloud Platform (GCP) environments
High proficiency in SQL and Python, paired with experience in one or more big data technologies (such as Google BigQuery, Redshift, or Snowflake)
Demonstrated success building and maintaining complex ETL/ELT pipelines, designing stored procedures, and optimizing complex queries for large-scale datasets
Practical familiarity with advanced data processing frameworks and architectures, including Dataflow, Pub/Sub, PySpark, Airflow, and open table formats (such as Iceberg or StarRocks)
Hands-on exposure to machine learning platforms (such as Vertex AI) or applied AI/ML pipelines is highly preferred
Solid understanding of operational workflows within the retail domain, along with beneficial familiarity handling clickstream data applications
Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related technical and quantitative discipline
Relevant industry certifications are highly beneficial (e.g., Google Professional Data Engineer, AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate)
Familiarity with structured IT frameworks, such as holding an ITIL Foundation asset designation
Superior problem-solving and critical thinking capabilities with a strong focus on process optimization, data profiling, and automation
Excellent verbal and written communication skills, with a proven ability to explain complex technical concepts to non-technical business partners
Outstanding organizational and time-management skills, with a track record of managing competing priorities and adapting quickly within fast-paced environments

Nice to have

Hands-on exposure to machine learning platforms (such as Vertex AI) or applied AI/ML pipelines
Familiarity handling clickstream data applications
Relevant industry certifications (e.g., Google Professional Data Engineer, AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate)
ITIL Foundation asset designation

What we offer

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

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Senior Data Engineer

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