Data Engineer

RAVL; Toronto; On-site; CAD 100,000 - 150,000; Full time

Benefits offered by this job

Flexible work model

Variable bonus & RRSP contributions

4 weeks paid time off

Paid professional development

Comprehensive health & dental coverage

Job summary

RAVL is looking for a Data Engineer in Toronto, Canada. In this role, you will design, build, and operate data pipelines to enable decision-making across organizations. Your work will involve transforming raw data into high-quality assets while collaborating closely with cross-functional teams.

This position offers competitive compensation ranging from $100,000 to $150,000 CAD, along with comprehensive health coverage, flexible work, and professional development opportunities. Join us to build better outcomes for our clients and your career.

Qualifications

• Strong experience designing and maintaining data pipelines using Spark, Airflow, or dbt.
• Proficiency in SQL and programming languages like Python, Java, or Scala.
• Hands-on experience with AWS, Azure, or GCP data ecosystems.

Responsibilities

• Design and build robust, scalable ETL/ELT data pipelines.
• Develop data models and architectures for analytics and reporting.
• Implement data ingestion, transformation, and quality checks.

Skills

Data pipeline design

SQL proficiency

Cloud data ecosystems

CI/CD for data workflows

Data governance

Tools

Spark

Airflow

AWS

Azure

GCP

Job description

RAVL helps technologists accelerate their careers. At RAVL, we connect strategy with execution, care deeply about the people we work with, and measure success by the lasting impact we leave behind. Our purpose is to build a team that puts real, sustainable business outcomes at the core of everything we do. We’re here to leave our clients better than we found them, and to create a place where our people are proud to Build. Better.

Role Overview

As a Data Engineer at RAVL, you’ll design, build, and operate the data pipelines and platforms that power decision-making for modern organizations. You’ll bring curiosity, technical depth, and a delivery-first mindset - transforming raw data into reliable, high-quality assets that enable insight, analytics, and machine learning. You’ll work across cloud environments, designing data systems that are resilient, secure, and built for scale.

What Success Looks Like In This Role

• Design and build robust, scalable ETL/ELT data pipelines using modern frameworks and cloud-native tooling
• Develop data models and architectures that enable efficient analytics and reporting
• Implement data ingestion, transformation, and quality checks across multiple sources and domains
• Leverage cloud services (AWS, Azure, or GCP) to design secure, cost-efficient, and maintainable data systems
• Work closely with platform and software engineers to integrate data flows into broader application ecosystems
• Ensure observability, reliability, and governance across pipelines and data products
• Collaborate with analysts, architects, and stakeholders to translate business requirements into technical data solutions
• At higher levels: mentor peers, contribute to data architecture decisions, and influence standards across teams

Sounds Great, But Do My Skills Fit?

• Strong experience designing and maintaining data pipelines using tools like Spark, Airflow, dbt, or similar
• Proficiency in SQL and one or more programming languages (Python, Java, or Scala)
• Hands-on experience with cloud data ecosystems - AWS (Glue, Redshift), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow). Understanding of modern data warehousing, streaming, and lakehouse architectures
• Experience with CI/CD for data workflows and version-controlled transformations
• Familiarity with data governance, cataloging, and security best practices
• Consulting excellence: communicates clearly, delivers visibly, and adapts to evolving business contexts

Mindset Traits

• Delivery-first – focuses on reliable, incremental progress toward business outcomes
• Structured and curious – thrives on understanding how data flows and enables value
• Collaborative – partners with cross-functional teams to align data and engineering efforts
• Influential – able to drive data quality and design conversations with technical and business peers

Technical Skills

• Languages: Python, SQL, and optionally Java or Scala
• Data Processing & Orchestration: Spark, dbt, Airflow, Kafka, or similar frameworks
• Cloud Platforms: AWS, Azure, or GCP (at least two preferred)
• Data Storage & Warehousing: Snowflake, Redshift, BigQuery, Databricks, Delta Lake
• CI/CD & Automation: GitHub Actions, Jenkins, or Azure DevOps for data workflows
• Security & Compliance: IAM, encryption, access control, and secure data handling

Why Join RAVL?

• Flexible, client-aligned work model – autonomy with accountability, adapting to client delivery needs
• Variable bonus & RRSP contributions tied to performance and delivery impact
• 4 weeks paid time off (plus public holidays)
• Paid professional development days and continuous learning opportunities
• Comprehensive health & dental coverage, including mental health support
• Commitment to lifelong learning – continuous improvement through training, mentorship, and certification

Compensation & Hiring Process

The salary range for this role is $100,000-$150,000 CAD, reflecting expected base pay. Total compensation may also include additional pay such as bonuses or incentives, depending on the position, and final offers are based on experience, skills, and qualifications. As part of our hiring process we may use technology, including AI-based tools, to help summarize and assess applications; these tools assist our team and do not replace human review or decision-making.

Equal Opportunity & Accessibility

RAVL is an equal opportunity employer committed to building a diverse, inclusive, and accessible workplace. We welcome applications from all qualified individuals and provide accommodations throughout the hiring process upon request. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.