Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake)
Optimize pipelines for performance, cost efficiency, and scalability within GCP
Develop batch and streaming data processes using Spark Streaming, and related technologies
Implement data solutions leveraging GCP services such as BigQuery, Cloud Storage, Dataflow, Cloud Composer, and Vertex AI integrations
Apply best practices for cloud security, IAM configuration, monitoring, and cost management
Build and maintain data models, including dimensional modeling and data vault structures
Implement data quality frameworks, validation rules, and automated testing
Manage data versioning, governance, and lineage using tools such as Unity Catalog or GCP Data Catalog
Partner with cross‑functional teams to gather requirements and translate them into technical designs
Provide technical guidance and influence engineering best practices across the team
Contribute to documentation, architectural diagrams, and knowledge sharing

3+ years of experience as a Data Engineer or similar role
Strong hands-on experience with Databricks, including: PySpark/Spark, Delta Lake, Databricks workflows/jobs
Proficiency with GCP: BigQuery, Cloud Storage, Dataflow or Dataproc
Strong coding skills in Python and SQL
Solid understanding of distributed systems, data warehousing, and data architecture principles
Experience with CI/CD tools (GitHub, GitLab, Azure DevOps, or similar)

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Data Engineer – Databricks, GCP

Key skills