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Data Modeller
- Toronto, ON, Canada
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- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Role: MongoDB Data Modeller
Location: Toronto, ON
Duration: Long Term Contract
Job Description:
MongoDB data modeller (JSON data modelling and schema creation).
5+ years of experience in JSON-based data modelling. Lead schema design to ensure data quality and performance.
Create XSD and JSON schemas. Lead MongoDB schema evolution, versioning, and migration. Rahona Data Engineer (data analytics ingestion and curation). Advanced proficiency with SQL query language.
Advanced proficiency in PySpark, including Spark SQL and performance optimization.
Minimum 2+ years of experience with Azure Cloud Development such as Azure Databricks (primary platform for PySpark), Azure Data Factory (ADF), Azure Synapse.
Strong knowledge of data ingestion, ETL processes, and orchestration frameworks for cloud environments.
Ability to design and manage data pipelines - extracting, transforming, and loading data - especially in cloud environments.
Soft Skills
Ability to work with business partners to gather data requirements. Strong analytical thinking, problem-solving, and troubleshooting abilities.
Self-motivated and proactive, with a keen eye for identifying opportunities for improvement and efficiency.
Excellent communication and documentation skills. NICE-TO-HAVE SKILLS: MongoDB data modeller (JSON data modelling and schema creation).
Apply MongoDB schema design patterns to develop scalable, performant data models.
Understand Confluent Kafka Schema Registry and how it influences schema design.
Experience with MongoDB indexing, sharding, and performance.
Experience with MongoDB Atlas in Azure. Rahona Data Engineer (data analytics ingestion and curation).
Knowledge of TD governance processes e.g., PIA, DAC. Familiarity with complying with audits and how processes should be set up so that audits go smoothly.
Domain Knowledge and Soft Skills.
Knowledge of the Payments domain. Awareness of ISO 20022 schemas in the Payments domain. Understanding data quality and lineage expectations for regulated environments.
Ability to work independently, research and explore new technologies, and develop solutions to complex problems while meeting timelines.
More about this job
Responsibilities
Lead MongoDB schema design, evolution, versioning, and migration, creating JSON and XSD schemas that support data quality and performance. Design and manage cloud data ingestion and ETL pipelines, using SQL and PySpark for analytics ingestion and curation.
Requirements
Requires at least five years of JSON-based data modeling experience, advanced SQL and PySpark proficiency, and at least two years of Azure cloud development experience. Candidates should also have strong knowledge of cloud data ingestion, ETL, orchestration, and pipeline design, along with analytical, communication, and documentation skills.
Skills
- MongoDB
- JSON Data Modeling
- Schema Design
- XSD
- SQL
- PySpark
- Spark SQL
- Azure Databricks
- Azure Data Factory
- Azure Synapse
- ETL
- Data Pipelines
- Data Ingestion
- Kafka Schema Registry
- MongoDB Indexing And Sharding
- Data Quality And Lineage
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
Keywords
- MongoDB
- JSON Data Modeling
- Schema Creation
- Schema Evolution
- Schema Versioning
- Schema Migration
- XSD
- SQL
- PySpark
- Spark SQL
- Azure Cloud
- Azure Databricks
- Azure Data Factory
- Azure Synapse
- Data Ingestion
- ETL
- Data Orchestration
- Data Pipelines
- Data Analytics
- Data Curation
- Confluent Kafka Schema Registry
- MongoDB Indexing
- MongoDB Sharding
- MongoDB Atlas
- Payments
- ISO 20022
- Data Governance
- Data Quality
- Data Lineage
- Audit Compliance