Data Engineer

HireTalent; Toronto; Hybrid; CAD 80,000 - 100,000; Full time

Job summary

A leading recruiting firm is seeking a Data Engineer to build and maintain scalable data infrastructure. In this role, you'll take ownership of data pipelines and collaborate with teams across the organization to enhance data quality and accessibility. The ideal candidate has over 3 years of experience, strong SQL and Python skills, and proficiency in ETL processes. This position is hybrid with opportunities for extension on a contract basis.

Qualifications

• 3+ years of professional experience in data engineering.
• Experience working with analytics, science, product, and engineering teams.
• Proficiency in SQL to understand complex business logic.
• Deep understanding of MPP systems and ETL processes.

Responsibilities

• Take ownership of core data pipelines, ensuring resilience and performance.
• Evolve data models and schemas to meet business requirements.
• Develop tools for self-service management of data pipelines.
• Conduct code reviews to uphold quality standards.

Skills

Data modeling

SQL

ETL processes

Data validation

Python

Collaboration

Tools

Airflow

Spark

Job description

Job Title: Data Engineer
Location: Remote / Hybrid – Toronto, Canada
Job Duration: 5+ Months Contract with Extension on T4

Description:
At ***, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
Here at ***, Data is the only way we make decisions. It is the core of our business, helping us create a transportation experience for our customers, and providing insights into the effectiveness of our product launch & features.
As a Data Engineer, you will play a key role in building and maintaining scalable data infrastructure at ***. You will join an early-stage team responsible for data transport, collection, and storage systems while exposing services that prioritize data as a first-class citizen. Your work will involve proposing innovative ideas, evaluating multiple approaches, and implementing solutions based on fundamental principles and supporting data.
You will take ownership of core data pipelines powering *** top-line metrics and collaborate with cross-functional teams to evolve data models and architectures. By architecting, building, and launching robust data pipelines, you will enable seamless access to insights that fuel critical functions such as Analytics, Data Science, and Engineering.
You will be part of *** core Marketplace team, focusing on developing pipelines that support decision-making processes for finance, pricing, and driver-related metrics. Your contributions will help data scientists make informed decisions that drive *** success.

Responsibilities:

• Take ownership of core data pipelines, ensuring resilience, optimal performance, timely delivery, data quality, and seamless onboarding of new features
• Continuously evolve data models and schemas to meet business and engineering requirements
• Implement and maintain systems to monitor and enhance data quality and consistency
• Develop tools that support self-service management of data pipelines (ETL) and perform SQL tuning to optimize data processing performance
• Contribute to the Data Engineering team’s technical roadmap, ensuring alignment with team and stakeholder goals
• Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency
• Conduct code reviews to uphold code quality standards and facilitate knowledge sharing
• Participate in on-call rotations to maintain high availability and reliability of workflows and data pipelines
• Collaborate with internal and external partners to remove blockers, provide support, and achieve results

Requirements:

• 3+ years of professional experience in data engineering
• Experience working directly with cross-functional stakeholders from analytics, science, product and engineering to align data solutions with business goals
• Proficiency in validation, explanation and visualization to present and analyze data and insights Strong skill in designing complex data model and resilient data pipelines that enrich them
• Proficiency in SQL being able to understand complex business logic and implement own one
• Deep understanding of how MPP systems process data and experience with ETL in Spark and/or similar
• Proficiency in writing data transformation scripting in Python, Java or similar Hands-on experience with workflow management tools (e.g., Airflow or similar)
• Proven ability to collaborate with cross-functional stakeholders (analytics, science, product, and engineering) to ensure data solutions align with business objectives
• Proficient in data validation, explanation, and visualization for effective data analysis and insight presentation Skilled in designing complex data models and resilient data pipelines
• Expertise in SQL, capable of understanding intricate business logic and implementing custom solutions
• Deep understanding of MPP systems and hands-on experience with ETL in Spark or similar technologies
• Proficient in writing data transformation scripts using Python, Java, or similar languages
• Practical experience with workflow management tools (e.g., Airflow, Flyte, etc.)