ML Engineer
About the role
Job Summary
We are seeking an experienced ML Engineer to build and optimize scalable data pipelines and machine learning solutions on Azure. The ideal candidate will have strong expertise in Azure Data Factory, Azure Databricks, Azure Machine Learning, PySpark, SQL, and Python , with experience developing cloud-based data engineering solutions.
Key Responsibilities
- Design and maintain scalable data pipelines using Azure Data Factory (ADF) .
- Develop ETL/ELT workflows using Azure Databricks and PySpark .
- Build and optimize data infrastructure for extracting, transforming, and loading large-scale datasets.
- Develop data solutions using SQL and Azure big data technologies.
- Collaborate with Product, Data Science, Design, and business teams to support data-driven initiatives.
- Build data tools and pipelines to enable analytics and machine learning workloads.
- Monitor, optimize, and enhance data platform performance and reliability.
Required Skills & Experience
- Strong hands-on experience with: Azure Data Factory (ADF)
- Azure Databricks
- Azure Machine Learning
- PySpark
- Python
- SQL
Experience with Azure Security , DevOps , and cloud-based data platforms.
Exposure to AWS is an asset.
Strong understanding of Spark, ETL processes, and modern data engineering practices.
Excellent analytical, problem-solving, and communication skills.
Ability to work collaboratively with cross-functional teams in an Agile environment.
This engagement is managed end-to-end by Querentia. Our recruiters give you honest feedback at every stage, prepare you for the interview, and support a smooth onboarding once you land the offer.