|
Описание: |
We are looking for a skilled Data Analyst to join our team and help us build a world-class data foundation. You will sit at the intersection of data engineering and business analysis, transforming raw data into high-quality, actionable datasets within our warehouse. Your goal is to establish a gold standard for our data assets, ensuring they are reliable, well-documented, and ready for strategic decision-making by Departments and Senior Management.
Requirements
* Expert SQL: Advanced proficiency in SQL (window functions, complex joins, indexing) and OLAP query optimization — 4+ years.
* Data Warehousing: Solid understanding of OLTP vs. OLAP and data modeling techniques.
* BI Development: Experience designing data sources and interactive dashboards in Metabase, Tableau, or similar tools.
* Systematic Thinking: Strong attention to detail and the ability to build scalable, logical systems.
* Requirement Formalization: Ability to gather and formalize requirements from stakeholders, even when they are not yet fully defined.
* Business Acumen: Focus on identifying business growth or risk drivers and preparing reports for senior management.
* Fluent Ukrainian, fluent Russian, English — upper intermediate or higher.
Responsibilities
* Design and implement analytics-ready data models using Fact/Dimension tables and semantic layers.
* Transform raw datasets into clean, structured Marts using dbt as the primary transformation tool.
* Ensure absolute consistency and logic alignment between the Data Warehouse (BigQuery) and the BI layer (Metabase).
* Write, test, and optimize complex SQL queries for advanced analytical use cases and reporting.
* Leverage Views and Materialized Views to improve performance and optimize BigQuery resource consumption.
* Partner with stakeholders (especially the Risk Dept) to translate business requirements into robust technical data models.
* Support and extend automated data ingestion flows from various sources using dlt.
* Manage and monitor the lifecycle of data assets and pipeline dependencies within Dagster.
* Define and standardize core business metrics and KPIs at the code level to ensure a “Single Source of Truth”.
* Implement automated data quality checks, validation rules, and proactive monitoring at the analytics layer.
* Document business logic, data definitions, and KPI catalogs for company-wide data discovery.
Nice to have
* Data Stack: Mandatory hands-on experience with dbt (models, tests, macros).
* Data Ingestion & Extraction: Practical experience with the dlt (data load tool) library or similar Python-based ingestion frameworks.
* Orchestration: Experience managing data workflows with Dagster (preferred) or similar orchestrators like Airflow/Prefect.
* Python: Proficiency in writing clean Python code for data manipulation and pipeline automation.
* Engineering Best Practices: Proficiency with Git (Pull Requests, Code Review), CI/CD, and Docker.
* FinTech Domain Experience: Previous experience working with financial transactions, digital wallets, or fraud detection systems.
Benefits
* Competitive and attractive compensation
* Remote work schedule
* Proper rest time of 24 annual leave days
* Challenging and unique tasks in the FinTech field
* Funding for gym memberships, fostering a healthy work-life balance
Interview Stages
* Interview with a Recruiter (1 hour)
* Interview with a Hiring Manager (1.5 hours)
Відгукнутись на вакансію |
