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Confiar Services

MongoDB Data Modeler / Data Engineer

Toronto, ON, Canada

$60 to $65 CAD / hour · Contract

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Job details

Pay: $60 to $65 CAD / hour
Job type: Contract
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

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.

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More about this job

Responsibilities

Design and optimize MongoDB data models, schemas, migrations, indexes, and performance, while developing scalable data pipelines with PySpark, SQL, and Azure services. Curate and integrate data from multiple sources, ensure quality and security, troubleshoot platform issues, document solutions, and collaborate with business and technology teams.

Requirements

Requires 5+ years of JSON-based data modeling and schema design, strong hands-on MongoDB experience, advanced SQL, and PySpark or Spark SQL expertise. Candidates must also have 2+ years of Azure Cloud experience, hands-on experience with Databricks, Data Factory, and Synapse, and knowledge of ETL/ELT, ingestion, orchestration, and MongoDB performance tuning.

Skills

MongoDB
JSON Data Modeling
Schema Design
SQL
PySpark
Spark SQL
Azure Databricks
Azure Data Factory
Azure Synapse Analytics
ETL/ELT
Data Ingestion
Data Pipelines
Data Curation
Data Quality
Indexing
Performance Optimization

Visa sponsorship

Not detected in the job text

Keywords

MongoDB
JSON
Data Modeling
Schema Design
XSD
Schema Evolution
Schema Versioning
Data Migration
Indexing
Performance Tuning
SQL
PySpark
Spark SQL
Azure Cloud
Azure Databricks
Azure Data Factory
Azure Synapse Analytics
ETL/ELT
Data Ingestion
Data Orchestration
Data Pipelines
Data Transformation
Data Integration
Data Cleansing
Data Curation
Data Quality
Data Lineage
Data Security
Banking

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