Qualifications Strong hands-on experience with Databricks (PySpark, Delta Lake, notebooks) – core requirement Proven ability to build and optimize ETL/ELT data pipelines in a lakehouse environment Experience with Azure Data Lake Storage (ADLS Gen2) for scalable data storage Hands-on development using Azure Data Factory (ADF) for orchestration and pipelines Experience with Azure Functions for serverless data processing Solid understanding of lakehouse architecture (Databricks + ADLS integration) Strong proficiency in Python and SQL for data transformation and pipeline logic Experience with data modeling, partitioning, and performance optimization Familiarity with Databricks Unity Catalog (data governance, access control) Experience integrating Databricks with Snowflake, APIs, or downstream BI systems Exposure to CI/CD pipelines (Azure DevOps, GitHub Actions) for data workflows Experience with infrastructure-as-code tools (Terraform or similar) is an asset Familiarity with orchestration tools (Airflow, dbt, or ADF pipelines) Strong communication skills with client-facing / consulting experience Databricks certifications preferred (strong indicator of hands-on expertise) #J-18808-Ljbffr
Databricks Engineer (Data Engineer)
MYTICAS CONSULTING
, , canada, , , canada
Published 27 days ago
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