Senior Data Engineer / Data Analyst - Connected Vehicle Analytics

Our client is seeking a highly collaborative and business-oriented Senior Data Engineer / Data Analyst to join their Analytics Data Team. Based out of Waterloo, ON on a Hybrid schedule (4 days per week in office), this senior role focuses on transforming complex, connected vehicle telemetry data into actionable insights that directly shape engineering, product, sales, and executive decisions.

In this role, you will serve as the vital bridge between vehicle embedded software engineers, technical product managers, and executive leadership. You will own the lifecycle of connected vehicle telemetry data—understanding how signals are instrumented, built, and transformed in production environments. Combining heavy data engineering capabilities (GCP, Python, SQL, ETL/ELT pipelines) with advanced statistical modeling and dashboard visualization, you will build trusted, scalable data solutions that accurately reflect real-world vehicle behavior and elevate the customer experience.

Advantages
Strategic Influence: Directly shape core engineering, product roadmaps, and executive-level business decisions for connected vehicle ecosystems.

Modern Cloud & Telemetry Stack: Work with high-volume, production-grade vehicle telemetry using Google Cloud Platform (GCP), Python, SQL, and advanced API ingestion models.

Cross-Domain Leadership: Act as a key technical liaison between embedded software developers, data scientists, and non-technical business leaders.

Advanced Analytical Scope: Apply sophisticated statistical methods—such as time-series analysis, regression models, and anomaly detection—to real-world vehicle signals.

Responsibilities
1. Business & Domain Partnership
Partner closely with vehicle embedded engineers, product owners, and technical product managers to understand how data is instrumented and generated within vehicle systems.

Translate loosely defined, complex business problems into scalable data solutions that yield measurable operational impact.

Apply rigorous statistical methods (hypothesis testing, correlation analysis, regression modeling) to validate assumptions and quantify relationships between vehicle signals and business metrics.

Translate technical data findings into business language for non-technical data consumers and stakeholders.

2. Data Engineering & Analytics Architecture
Design, construct, and maintain scalable, production-grade data pipelines handling high-volume structured and semi-structured telemetry data.

Build statistical and analytical models in SQL, Python, or R to conduct trend analysis, anomaly detection, and driver/vehicle behavior studies.

Implement robust ETL/ELT workflows across diverse data types, time-series data streams, and ingestion protocols (e.g., OAuth-based APIs).

Apply multivariate analysis and regression to identify key drivers of system performance and overall customer experience.

3. Data Quality, Validation & Lineage
Investigate and validate upstream data quality before deploying analytical models into production.

Perform root-cause analysis on data inconsistencies related to physical vehicle signal instrumentation and mapping.

Establish automated monitoring and validation frameworks to ensure high data integrity, accuracy, and platform reliability.

Collaborate with upstream system owners to resolve data lineage, schema drift, and signal mapping discrepancies.

4. Visualization & Executive Communication
Design, build, and deploy executive-ready dashboards using tools such as Power BI or LookerStudio.

Communicate complex technical insights clearly, focusing on business impact and strategic value.

Present analytical findings and data solution demonstrations during business audience reviews and executive briefings.

Qualifications
Core Experience & Education
Education: Bachelor’s degree in Data Engineering, Computer Science, Statistics, Information Systems, or a related quantitative field.

Tenure: 10+ years of dedicated Data Engineering and analytics experience working with enterprise-level data environments.

Technical Depth: 5+ years of hands-on expertise with SQL, Google Cloud Platform (GCP), Python, and relational database modeling.

Technical Skillset Matrix
Languages & Modeling: Advanced proficiency in SQL and Python (or R) for data transformation, statistical analysis, and pipeline development.

Cloud Infrastructure: Solid experience building and managing data solutions on Google Cloud Platform (GCP).

Database & Pipeline Design: Deep understanding of database design, relational databases, data modeling, data integrity frameworks, and ETL/ELT pipeline construction.

Data Ingestion: Experience working with high-volume, noisy telemetry data, time-series streams, and API ingestion mechanisms.

Visualization Tools: Hands-on experience developing executive dashboards in Power BI, LookerStudio, or equivalent analytics platforms.

Statistical & Analytical Methods
Practical application of hypothesis testing, regression modeling, time-series analysis, correlation analysis, and multivariate analysis on large-scale datasets.

Summary
Our client is seeking a highly collaborative and business-oriented Senior Data Engineer / Data Analyst to join the FNV Analytics Data Team. Based out of Waterloo, ON on a Hybrid schedule (4 days per week in office), this senior role focuses on transforming complex, connected vehicle telemetry data into actionable insights that directly shape engineering, product, sales, and executive decisions.

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 accessibility@randstad.ca to ensure their ability to fully participate in the interview process.