Databricks Engineer (Data Engineer) (Toronto)

Databricks Engineer (Data Engineer) (Toronto)

19 Apr
|
Myticas Consulting
|
Toronto

19 Apr

Myticas Consulting

Toronto

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 setting

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) (Toronto)
🏢 Myticas Consulting
📍 Toronto

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