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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