Closed listing
MongoDB Data Modeler / Data Engineer
- Toronto, ON, Canada
$55 to $60 CAD / hour · Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Pay
- $55 to $60 CAD / hour
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
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.
More about this job
Responsibilities
Design and optimize MongoDB data models and schemas, and develop scalable data ingestion and ETL/ELT pipelines using PySpark, SQL, and Azure platforms. Ensure data quality, lineage, and performance; collaborate with stakeholders, troubleshoot issues, and document data models and technical processes.
Requirements
Requires 5+ years of JSON-based data modeling and MongoDB experience, advanced SQL and PySpark/Spark SQL skills, and 2+ years of Azure experience with Databricks, Data Factory, and Synapse. Candidates should understand cloud data pipelines, ingestion, ETL/ELT, and orchestration, with strong analytical, communication, and documentation skills.
Skills
- JSON Data Modeling
- MongoDB
- Schema Design
- PySpark
- Spark SQL
- SQL
- Azure Databricks
- Azure Data Factory
- Azure Synapse Analytics
- ETL/ELT
- Data Ingestion
- Data Pipeline Development
- Data Quality
- Data Lineage
- MongoDB Indexing
- Schema Evolution
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
- Consulting
Keywords
- MongoDB
- JSON
- XSD
- PySpark
- Spark SQL
- SQL
- Azure
- Azure Databricks
- Azure Data Factory
- Azure Synapse Analytics
- ETL/ELT
- Data Ingestion
- Data Pipelines
- Schema Design
- Schema Evolution
- Schema Versioning
- Data Migration
- Indexing
- Performance Optimization
- Data Quality
- Data Lineage
- Data Governance
- Data Orchestration
- MongoDB Atlas
- Kafka
- Confluent Schema Registry
- Sharding
- Payments
- ISO 20022
- Audit Processes