Engineer building scalable data platforms for commercial trucking API company. Designing and optimizing the data platform to tackle complex backend challenges.
About the role
- Data Engineer at RAVL designing, building, and operating data pipelines for decision-making. Transforming raw data into reliable assets for analytics and machine learning.
Responsibilities
- 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
Requirements
- 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.
Benefits
- 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.
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