Senior Data Analyst

👉 We are considering citizens of the Russian Federation and Armenia who reside in Armenia.

✅We are looking for a Senior Data Analyst in Armenia.

💼About the project: We are building a Customer Intelligence & Personalization Platform for an ecosystem of businesses in Armenia. At its core is the Golden Record: a unified customer profile that combines data from the bank, ecosystem products, and external sources.

🦸Role tasks: The task is to design the layer between the raw data of the core banking system and the platform's data marts. The source is poorly documented: some values are coded, some business logic is implemented in code and stored procedures, two outwardly identical records can be assembled by different algorithms from different tables.

We need a person who will decipher this source and transform it into a meaningful data model: what comes from where, what influences what, which field means what.

⚙️What needs to be done: ● Explore the core banking system, legacy and external sources, and restore their semantics. ● Work from the target data mart to the source: determine which tables and based on what logic each attribute is collected. ● Separate cases where data that looks identical is obtained through different paths, and document the selection rules. ● Describe the data model and metadata: entities, relationships, grain, keys, historicity. ● Formulate requirements for data marts for segmentation, scoring, and recommendations. ● Write SQL research and transformation prototypes, test hypotheses on data. ● Find out the meaning of the data directly from bank employees — this is a constant part of the job.

‼️If you have worked as a data engineer and spent a significant portion of your time understanding what is in the source, then you are our profile. If you received ready-made clean data marts, then probably not.

🏆AI-native approach: We use an AI-native approach and expect the same from the candidate: AI tools are used for deciphering legacy systems, analyzing schemas, writing SQL, and documentation.

🛠Requirements: ● Strong SQL: window functions, complex join chains, quality and distribution analysis. ● Experience in reverse-engineering poorly documented sources. ● Understanding of data modeling: entities, grain, keys, historicity, master entities. ● Experience with banking or fintech data (Core banking (especially ArmSoft) / legacy banking systems, Customer 360) or experience in deciphering raw banking data about customers and products from poorly documented systems for the purpose of producing marketing and financial analytics. ● Python at the data exploration level. ● Ability to independently bring a task from 'here's the raw data, here's the target data mart' to completion. ● Proactivity: readiness to find out the meaning of data from people, not wait for documentation. ● Git, Linux, experience working in closed Dev/UAT environments.

🤝Conditions: Interaction via Individual Entrepreneur (IE) Location - Armenia Work format - hybrid, willingness to work from the bank's office up to 3 times a week.