We are seeking an experienced Python Developer with a strong background in the banking or financial services domain. The ideal candidate will have hands-on experience building and maintaining data pipelines, feature engineering workflows, and data cleansing solutions to support analytics, predictive modeling, and banking operations.

This role is critical in ensuring high-quality, scalable, and efficient data solutions that drive business insights and operational decision-making.

• Design, develop, and maintain scalable Python-based data 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, supporting both real-time and batch processing.
  

  
  

• Collaborate with data scientists and analysts to develop feature engineering solutions for credit risk, fraud detection, and customer analytics.
  

• Transform raw banking data into meaningful features to enhance predictive model performance.
  

• Create and maintain feature stores and reusable pipelines to support ML initiatives.
  

  
  

• Implement data validation frameworks and cleansing routines to ensure accuracy, consistency, and completeness.
  

• Identify and resolve data quality issues, including missing values, duplicates, outliers, and inconsistencies.
  

• Develop automated data quality monitoring and alerting systems.
  

  
  

• Write clean, efficient, and well-documented Python code following industry best practices.
  

• Develop and maintain APIs and microservices for data access and integration.
  

• Implement unit tests, integration tests, and participate in code reviews to ensure high-quality deliverables.
  

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field (or equivalent practical experience).
  

• Minimum 5 years of professional Python development experience.
  

• Proven experience in banking, financial services, or fintech, with understanding of banking products, processes, and regulations.
  

  
  

• Expert-level Python programming with libraries such as pandas, NumPy.
  

• Hands-on experience in feature engineering (encoding, scaling, binning, transformations, dimensionality reduction).
  

• Expertise in data cleansing and validation methodologies.
  

• Proficiency with SQL and relational databases (PostgreSQL, MySQL, Oracle).
  

• Experience with version control (Git) and CI/CD pipelines.
  

  
  

• Strong understanding of banking concepts: retail/corporate banking, payments, lending, or risk management.
  

• Knowledge of banking data structures, transaction processing, and regulatory reporting.
  

• Awareness of data privacy and compliance standards (e.g., GDPR, PCI-DSS, Basel III).
  

• Experience with ML model deployment and MLOps practices.
  

• Familiarity with data visualization tools (Tableau, Power BI, matplotlib, seaborn, plotly).
  

• Understanding of software design patterns and architectural principles.
  

• Exposure to Agile/Scrum methodologies.