Risk Engineerinng - Python- Data Engineers - Manager

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RCE-Risk Data Engineer-Leads

Job Description: -
Our Technology team builds innovative digital solutions rapidly and at scale to deliver the next generation of Financial and Non- Financial services across the globe.
The Position is a senior technical, hands-on delivery role, requiring the knowledge of data engineering, cloud infrastructure and platform engineering, platform operations and production support using ground-breaking cloud and big data technologies. 
The ideal candidate with 8-10 years of relevant experience, will possess strong technical skills, an eagerness to learn, a keen interest on 3 keys pillars that our team support i.e. Financial Crime, Financial Risk and Compliance technology transformation, the ability to work collaboratively in fast-paced environment, and an aptitude for picking up new tools and techniques on the job, building on existing skillsets as a foundation. 
In this role you will: 

• Develop, maintain and optimize backend systems and RESTFul APIs using Python and Flask
• Proficient in concurrent processing strategies and performance optimization for complex architectures 
• Write clean, maintainable and well-documented code
• Develop comprehensive test suites to ensure code quality and reliability 
• Work independently to deliver features and fix issues, with a few hours of overlap for real-time collaboration 
• Integrate backend services with databases and APIs
• Collaborate asynchronously with cross functional team members
• Participate in occasional team meetings, code reviews and planning sessions.

Core/Must Have skills. 

• Should have minimum 6+ years of Professional Python Development experience. 
• Should have Strong understanding of Computer science fundamentals (Data Structures, Algorithms).
• Should have 6+ years of experience in Flask and Restful API Development 
• Should possess Knowledge on container technologies (Dockers, Kubernetes)
• Should possess experience on implementing interfaces in Python
• Should know how to use python generators for efficient memory management.
• Should have good understanding of Pandas, NumPy and Matplotlib library for data analytics and reporting. 
• Should know how to implement multi-threading and enforce parallelism in python.
• Should know to various.
• Should know to how to use Global interpreter lock (GIL) in python and its implications on multithreading and multiprocessing.
• Should have a good understanding of SQL alchemy to interact with databases.
• Should posses’ knowledge on implementing ETL transformations using python libraries.
• Collaborate with cross-functional teams to ensure successful implementation techniques of performing list compressions in python of solutions.

Good to have:

• Exposure to Data Science libraries or data-centric development 
• Understanding of authentication and authorization (e.g. JWT, OAuth)
• Basic knowledge of frontend technologies (HTML/CSS/JavaScript) is a bonus but not required.
• Experience with cloud services (AWS, GCP or Azure)

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