Closed listing
MongoDB Data Modeler / Data Engineer
- Toronto, ON, Canada
$60 to $65 CAD / hour · Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Pay
- $60 to $65 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.
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.
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
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
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