Data Engineer

Lime Lime · Consumer · Canada · Engineering

Data Engineer at Lime responsible for architecting, building, and scaling data infrastructure for analytics, machine learning models, and business intelligence. Focuses on ETL/ELT pipelines, data transformations, data ops, reliability, and governance.

What you'd actually do

  1. Design, build, and maintain high-throughput ETL/ELT pipelines for data ingestion, processing, and storage solutions.
  2. Develop complex, performance-tuned data transformations using Python, high-performance SQL, and tools like dbt.
  3. Contribute to our technical strategy and how we can scale to support future business needs
  4. Implement data ops best practices, including CI/CD for data pipelines, version-controlled schemas (dbt), and automated testing.
  5. Help drive data reliability and observability strategy, including improving data quality and lineage tracking.

Skills

Required

  • 2+ years of experience in data engineering and distributed systems.
  • Hands-on experience building and scaling data stacks on cloud providers (AWS preferred), including experience with Snowflake.
  • Expertise in developing and debugging complex data transformations using Python and high-performance SQL.
  • Experience with workflow orchestration tools such as Airflow.
  • Familiarity with distributed processing technologies like Spark, Flink, or Kafka.
  • Understanding of data modeling, ETL pipelines, and experience with data transformation tools like dbt.
  • Familiarity with modern data governance tools and practices (cataloging, lineage, and PII masking).
  • Experience with Iceberg, Debezium, or Infrastructure-as-Code tools like Terraform for managing data infrastructure.

Nice to have

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.