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Senior Data Engineer / Data Modeler – Banking Domain

  • Toronto, ON, Canada

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This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Contract
Closing date
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

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; translate business requirements into data solutions; and optimize pipelines for performance and scalability.

Requirements

Requires 8+ 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 domain experience, knowledge of conceptual, logical, physical, and dimensional modeling, and experience with large-scale data processing and modern data platforms.

Skills

  • Python
  • PySpark
  • SQL
  • SQL Data Modeling
  • JSON Data Modeling
  • Data Engineering
  • Data Modeling
  • ETL/ELT
  • Dimensional Modeling
  • Data Warehousing
  • Data Transformation
  • Data Integration
  • Data Mapping
  • Data Quality Validation
  • Large-Scale Data Processing
  • Azure

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software
  • Finance & Accounting
  • Consulting

Keywords

  • Data Engineering
  • Data Modeling
  • Banking
  • Financial Services
  • Python
  • PySpark
  • SQL
  • JSON Data Modeling
  • ETL/ELT
  • Azure
  • Conceptual Data Modeling
  • Logical Data Modeling
  • Physical Data Modeling
  • Dimensional Modeling
  • Data Warehousing
  • Data Pipelines
  • Data Transformation
  • Data Integration
  • Data Mapping
  • Data Quality Validation
  • Large-Scale Data Processing
  • Modern Data Platforms
  • Performance Optimization
  • Scalability

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