Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
Title – Python Developer 10 + years exp and Banking exp
Location – Toronto, ON (Mandate 4 days onsite)
Note – In-person interview is mandatory
We are seeking an experienced Python Developer with a strong background in the banking sector to join our team. The ideal candidate will bring 5 years of hands-on Python development experience combined with expertise in data processing, feature engineering, and data cleansing. This role is critical in building and maintaining robust data pipelines and analytical solutions that support our banking operations and decision-making processes.
Key Responsibilities
Data Engineering & Processing
- Design, develop, and maintain scalable Python-based data processing pipelines to handle large volumes of banking data including transactions, customer information, and financial records
- Implement efficient ETL (Extract, Transform, Load) processes to integrate data from multiple banking systems and external sources
- Optimize data workflows for performance, reliability, and scalability to support real-time and batch processing requirements
Feature Engineering & Model Support
- Collaborate with data scientists and analysts to develop sophisticated feature engineering solutions for credit risk models, fraud detection systems, and customer analytics
- Transform raw banking data into meaningful features that enhance predictive model performance
- Create and maintain feature stores and reusable feature pipelines to support machine learning initiatives
Data Quality & Cleansing
- Implement comprehensive data validation frameworks and cleansing routines to ensure data accuracy, consistency, and completeness
- Identify and resolve data quality issues including missing values, outliers, duplicates, and inconsistencies in banking datasets
- Develop automated data quality monitoring and alerting systems to proactively detect and address data anomalies
Technical Development
- Write clean, efficient, and well-documented Python code following industry best practices and internal coding standards
- Develop and maintain APIs and microservices to support data access and integration across the organization
- Implement unit tests, integration tests, and participate in code reviews to ensure code quality and reliability
Required Qualifications
Experience & Education
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field (or equivalent practical experience)
- Minimum 6 years of professional experience in Python development
- Proven experience working in the banking, financial services, or fintech industry with understanding of banking products, processes, and regulatory requirements
Technical Skills
- Expert-level proficiency in Python and its data ecosystem including pandas, NumPy
- Strong experience with data processing.
- Hands-on experience with feature engineering techniques including encoding, scaling, binning, transformation, and dimensionality reduction
- Demonstrated expertise in data cleansing methodologies including handling missing data, outlier detection, data normalization, and validation
- Proficiency with SQL and experience working with relational databases (PostgreSQL, MySQL, Oracle)
- Experience with version control systems (Git) and CI/CD pipelines
Domain Knowledge
- Strong understanding of banking domain concepts including retail banking, corporate banking, payments, lending, or risk management
- Knowledge of banking data structures, transaction processing, and regulatory reporting requirements
- Awareness of data privacy regulations and compliance standards relevant to banking (e.g., GDPR, PCI-DSS, Basel III)
Preferred Qualifications
- Experience with machine learning model deployment and MLOps practices
- Familiarity with data visualization tools such as Tableau, Power BI, or Python libraries (matplotlib, seaborn, plotly)
- Understanding of software design patterns and architectural principles
- Exposure to Agile/Scrum development methodologies
Key Skills
Ranked by relevanceReady to apply?
Join VLink Inc and take your career to the next level!
Application takes less than 5 minutes

