Role Overview
They are looking for MongoDB Data Modeler / Data Engineer to support Canada’s data analytics, ingestion, and data curation initiatives. The ideal candidate will have strong experience in MongoDB, JSON data modeling, SQL, PySpark, and Azure data platforms.
Key Responsibilities
- Design and develop MongoDB JSON data models, schemas, and XSD/JSON schemas.
- Lead MongoDB schema evolution, versioning, migration, indexing, and performance optimization.
- Develop and optimize data pipelines using PySpark, Spark SQL, and SQL.
- Build and manage ETL/ELT and data ingestion pipelines using Azure Databricks, Azure Data Factory (ADF), and Azure Synapse.
- Perform data transformation, integration, cleansing, and curation across multiple data sources.
- Ensure data quality, lineage, scalability, security, and performance across data platforms.
- Collaborate with business analysts, data engineers, architects, and technology teams to gather requirements and deliver data solutions.
- Troubleshoot data pipeline and MongoDB performance issues.
- Maintain technical documentation related to data models, schemas, pipelines, and data flows.
Must-Have Skills
- 5+ years of experience in JSON-based data modeling and schema design.
- Strong hands-on experience with MongoDB.
- Advanced SQL skills.
- Strong experience with PySpark / Spark SQL.
- 2+ years of Azure Cloud experience.
- Hands-on experience with:
- Azure Databricks
- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Strong understanding of ETL/ELT, data ingestion, orchestration, and cloud data pipelines.
- Experience with MongoDB schema design, indexing, migration, and performance tuning.
- Strong analytical, communication, and documentation skills.
