Senior Data Engineer/ Data Modeler
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
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- Posting language
- English
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Original job description
Senior Data Engineer / Data Modeler – Banking Domain
Experience: 8+ Years | Location: Toronto, ON – Hybrid | Duration: 6–12 Months
Cloud: Azure
Role Overview: We are looking for a hands-on Senior Data Engineer / Data Modeler with strong expertise in both Data Engineering and Data Modeling. The consultant must have excellent Python and PySpark coding skills, strong SQL/Data Modeling experience, and experience working in the Banking/Financial Services domain.
Key Responsibilities
- Design conceptual, logical, and physical data models for banking data.
- Develop and optimize scalable data pipelines using Python, PySpark, and SQL.
- Perform SQL Data Modeling and JSON Data Modeling for structured and semi-structured data.
- Perform data transformation, integration, mapping, and quality validation.
- Translate business requirements into data models and engineering solutions.
- Write, optimize, and troubleshoot Python and PySpark code for large-scale data processing.
- Optimize data processing and troubleshoot pipelines for performance and scalability.
Mandatory Skills
- 8+ years of experience in Data Engineering and Data Modeling.
- Strong hands-on coding experience in Python.
- Strong hands-on coding experience in PySpark.
- Strong SQL Data Modeling / JSON Data Modeling experience.
- Strong SQL and ETL/ELT experience.
- Strong knowledge of conceptual, logical, and physical data modeling.
- Experience with dimensional modeling and data warehouse concepts.
- Strong Banking/Financial Services domain experience.
- Experience with large-scale data processing and modern data platforms.
Ideal Candidate: We are looking for one consultant who can perform both Data Modeling and Data Engineering, with a strong emphasis on hands-on Python and PySpark development. The candidate should have practical experience with SQL and JSON data modeling. This is not a pure Data Modeler role.
More about this job
Responsibilities
Design conceptual, logical, and physical data models for banking data, and develop scalable data pipelines using Python, PySpark, and SQL. Transform, integrate, map, and validate data while translating business requirements into engineering solutions and optimizing pipeline performance.
Requirements
Requires 8 or more years of experience in data engineering and data modeling, with strong hands-on Python, PySpark, SQL, and ETL/ELT skills. Candidates must have banking or financial services experience, knowledge of dimensional modeling and data warehousing, and practical experience with structured and semi-structured data.
Skills
- Python
- PySpark
- SQL
- Data Modeling
- JSON Data Modeling
- Data Engineering
- ETL/ELT
- Dimensional Modeling
- Data Warehousing
- Data Pipelines
- Data Transformation
- Data Integration
- Data Mapping
- Data Quality Validation
- Large-Scale Data Processing
- Azure
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Banking
- Financial Services
- Azure
- Python
- PySpark
- SQL
- JSON
- Data Engineering
- Data Modeling
- Conceptual Data Modeling
- Logical Data Modeling
- Physical Data Modeling
- Dimensional Modeling
- Data Warehousing
- ETL
- ELT
- Data Pipelines
- Data Transformation
- Data Integration
- Data Mapping
- Data Quality Validation
- Structured Data
- Semi-Structured Data
- Large-Scale Data Processing
- Performance Optimization
- Scalability
- Business Requirements