MongoDB Data Modeler / Data Engineer
location: Toronto, Canada
Duration: Long Term Contract
Role Overview
We are looking for an experienced MongoDB Data Modeler / Data Engineer to support data analytics, ingestion, and curation initiatives. The ideal candidate will have strong expertise in JSON/MongoDB schema design, PySpark, SQL, and Azure data platforms, along with hands-on experience building scalable data pipelines.
Key Responsibilities
- Design and develop MongoDB JSON data models, schemas, and XSD/JSON schemas.
- Manage MongoDB schema evolution, versioning, migration, indexing, and performance optimization.
- Develop and optimize data pipelines using PySpark, Spark SQL, and SQL.
- Build and maintain cloud-based ETL/ELT and data ingestion pipelines using Azure Databricks, ADF, and Synapse.
- Ensure data quality, lineage, scalability, and performance across data platforms.
- Collaborate with business and technology teams to gather requirements and deliver effective data solutions.
- Troubleshoot data pipeline and performance issues and implement appropriate solutions.
- Document data models, schemas, mappings, pipelines, and technical processes.
Must-Have Skills
- 5+ years of experience in JSON-based data modeling and schema design.
- Strong hands-on experience with MongoDB.
- Advanced SQL and PySpark/Spark SQL skills.
- 2+ years of Azure Cloud experience, particularly with:
- Azure Databricks
- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Strong understanding of data ingestion, ETL/ELT, orchestration, and cloud data pipelines.
- Experience with MongoDB schema design, data modeling, and optimization.
- Strong analytical, communication, and documentation skills.
Nice-to-Have Skills
- Experience with MongoDB Atlas on Azure.
- Experience with Kafka / Confluent Schema Registry.
- Knowledge of MongoDB indexing, sharding, and performance tuning.
- Experience in the Payments domain or ISO 20022.
- Experience with data governance, data quality, data lineage, and audit processes.
