Description
We invite you to join a project aimed at implementing a comprehensive solution for individualizing pricing for retail banking products. Our goal is to create an autonomous calculation system for analyzing scenarios, finding the optimal scenario, and its implementation through an individual offer to the client using autonomous AI agents. We want to build a cutting-edge ecosystem in the Russian Federation with a fundamentally new customer experience.
Key areas: individualization of pricing offers for retail loan products, debit and credit cards, deposits, current accounts, investment products, subscription lines and packages; creation of an IT solution for managing limits and authorities of the bank's sales divisions; creation of tools for calculating the economic efficiency of financial pilots.
Responsibilities
- designing and implementing high-load distributed solutions based on Apache Spark
- developing batch and streaming ETL processes
- supporting the architecture of corporate data warehouses (DWH, Data Lake, LakeHouse)
- creating and optimizing queries using SQL and Spark SQL
- participating in architecture sessions and designing system architecture
- conducting code reviews, ensuring compliance with coding standards.
Requirements
- at least 3 years of development experience in Python, using pySpark
- experience working with Python data frameworks (Pandas/Numpy)
- understanding of SDLC principles and practical experience creating Python applications using distributed computing, understanding of OOP principles, SOLID, design patterns
- excellent knowledge of SQL (Advanced) and experience in data analytics (DWH, Data Lake, Lake House)
- experience in building ETL
- experience working with AI tools to improve efficiency
understanding of CI/CD principles, quality assurance approaches.
Will be a plus:
- skills in working with generative AI models; experience in creating AI agents and using them in work will be an advantage
- experience with Kafka, integration interactions (HTTP, REST, GraphQL)
- experience with Docker, Kubernetes
- understanding of Machine Learning (ML) basics
- desire to develop skills in genAI technologies (Agentic, RAG etc.).
Conditions
- only hybrid work format, Moscow, St. Petersburg, Samara
- annual bonus and annual salary review
- extended health insurance from day one and preferential insurance for family
- Sber Corporate University, internal educational platform, participation in IT conferences
- flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- free SberPrime+ subscription, discounts on partner company products
- referral bonus for recommending friends to the team.
