MongoDB Data Modeler / Data Engineer

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 .