Design, build, and optimize Databricks-based data and ML platforms. Own ETL pipelines, Delta Lake lakehouse, MLflow model lifecycle, MLOps, cluster optimization, RAG/LLM solutions, BI integration, and data governance with Unity Catalog.
Job Summary
We are seeking a highly skilled Databricks Engineer with
AI/ML experience to design, build, and optimize scalable data and machine
learning platforms on Databricks. The role involves end-to-end ownership of
data pipelines, ML workflows, and production AI systems.
Key Responsibilities
- Design
and implement scalable ETL pipelines using Databricks & Spark
- Build
Lakehouse architecture using Delta Lake
- Develop
and deploy ML models using MLflow
- Implement
MLOps pipelines for training, testing, and serving models
- Optimize
cluster performance and reduce compute cost
- Build
RAG and LLM-based solutions using Mosaic AI
- Integrate
analytics with BI tools (Power BI, Tableau)
- Implement
data governance using Unity Catalog
- Collaborate
with Data Scientists and Business teams
- Ensure
data quality, security, and compliance
Required Skills
Mandatory
- 5+
years of Databricks & Apache Spark
- Strong
Python & PySpark
- Experience
with Delta Lake & Lakehouse
- MLflow
& MLOps experience
- Cloud
platform (AWS/Azure/GCP)
- Git
& CI/CD
Preferred
- Experience
with LLMs & Generative AI
- RAG
pipelines & Vector Databases
- Deep
Learning frameworks
- Databricks
certifications
- Power
BI integration
Requirements
Job Summary
We are seeking a highly skilled Databricks Engineer with
AI/ML experience to design, build, and optimize scalable data and machine
learning platforms on Databricks. The role involves end-to-end ownership of
data pipelines, ML workflows, and production AI systems.
Key Responsibilities
- Design
and implement scalable ETL pipelines using Databricks & Spark
- Build
Lakehouse architecture using Delta Lake
- Develop
and deploy ML models using MLflow
- Implement
MLOps pipelines for training, testing, and serving models
- Optimize
cluster performance and reduce compute cost
- Build
RAG and LLM-based solutions using Mosaic AI
- Integrate
analytics with BI tools (Power BI, Tableau)
- Implement
data governance using Unity Catalog
- Collaborate
with Data Scientists and Business teams
- Ensure
data quality, security, and compliance
Required Skills
Mandatory
- 5+
years of Databricks & Apache Spark
- Strong
Python & PySpark
- Experience
with Delta Lake & Lakehouse
- MLflow
& MLOps experience
- Cloud
platform (AWS/Azure/GCP)
- Git
& CI/CD
Preferred
- Experience
with LLMs & Generative AI
- RAG
pipelines & Vector Databases
- Deep
Learning frameworks
- Databricks
certifications
- Power
BI integration
What you need to know about the Ottawa Tech Scene
The capital city of Canada and the nation's fourth-largest urban area, Ottawa has proven a rapidly growing global tech hub. With over 1,800 tech companies, many of which are leaders in their sectors, the city's tech talent now makes up more than 13 percent of its total workforce. This growth is driven not only by the big players like UL Solutions and Dropbox, but also by a thriving startup ecosystem, as new businesses emerge to follow in the footsteps of those that came before them.
