Senior Data Analyst in Armenia

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

💼About the project: We are building a Customer Intelligence & Personalization Platform for the ecosystem of businesses in Armenia. At its core is the Golden Record: a unified client profile combining data from the bank, ecosystem products, and external sources. On top of this, we build Customer 360, segmentation, scoring, and personalized offers.

🦸Role responsibilities: You will need 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 encoded, some business logic is implemented in code and stored procedures, and two outwardly identical records can be assembled by different algorithms from different tables.

We need someone who can untangle this source and transform it into a conceptual data model: what comes from where, what influences what, what a field means.

⚙️What you will do: ● Explore the core banking system, legacy and external sources, and restore their semantics. ● Work from the target data mart back to the source: determine which tables and logic are used to assemble each attribute. ● Differentiate cases where data of the same appearance 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 investigations and transformation prototypes, test hypotheses with data. ● Find out the meaning of data directly from bank employees — this is a constant part of the job.

About your background: What tasks you have solved is important — you came into an unfamiliar, undocumented system and figured it out yourself, restored the business meaning of the data, built a model from scratch and brought the investigation to a working data mart.

‼️If you have worked as a data engineer and spent a significant amount of time understanding what is in the source, 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 legacy analysis, schema analysis, SQL writing, 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 analyzing raw banking data about clients and products from poorly documented systems for the purpose of producing marketing and financial analytics. ● Python at the data exploration level. ● Ability to independently complete a task from "here is the raw data, here is the target data mart" to a result. ● Proactiveness: willingness to find out the meaning of data from people, not wait for documentation. ● Git, Linux, experience working in closed Dev/UAT environments.

🎯Will be a plus: · Knowledge of Armenian language · Matching and deduplication methodologies · Experience with Data Vault 2.0 · Experience with DBT or similar · PII, masking, RBAC · Experience in a regulated on-premise environment · Expertise in ML, ML Ops

🤝Conditions: Interaction under an Individual Entrepreneur agreement Location - Armenia Work format - hybrid, with the readiness to work from the bank's office up to 3 times a week.