Advanced Python Programming: Extensive experience with Python, including proficiency in asynchronous programming, multithreading, and multiprocessing.
API Development and Integration: Strong experience in building and consuming RESTful APIs and familiarity with GraphQL.
Data Manipulation and Analysis: Proficiency with libraries such as Pandas, NumPy, and SQLAlchemy for data manipulation and analysis.
Plugin/Extension Development: Experience in developing plugins or extensions for data visualization tools like PowerBI, Tableau, or similar.
Data Access and Security: Understanding of OAuth, SAML, and other authentication protocols, with experience in implementing secure data access solutions.
Database Management: Proficiency with both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
Cloud Services: Experience with cloud platforms such as AWS, Azure, or Google Cloud, including services like Lambda, EC2, and S3.
Containerization and Orchestration: Familiarity with Docker and Kubernetes for containerization and orchestration of applications.
Version Control and CI/CD: Strong experience with Git and CI/CD pipelines using tools like Jenkins, GitLab CI, or GitHub Actions.
Testing Frameworks: Proficiency in using testing frameworks such as PyTest, Unittest, or Nose for automated testing.
Preferred skills:
Data Visualization: PowerBI DAX, Power Query, Power BI API for customizations
Agile Methodologies: Scrum / Kanban frameworks
Machine Learning and AI: Machine learning frameworks: TensorFlow, PyTorch
Job Classification
Industry: BankingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data Platform EngineerEmployement Type: Full time