Middle/Middle+ Data Analyst (SQL / Python / BI / LLM)

Vacancy ID: 92459_SS
Rate: to be discussed.
Grade: Middle / Middle+.
Workload: Full-time (полная занятость).
Engagement Term: 24 months with the possibility of extension.
Format: Remote.
Time Zone: UTC+3 (MSK).
Location/Citizenship: Russian Federation / Russian Federation.
⏳ 🚨 URGENT: Vacancy is active until 10.27 inclusive until 17:00! 🚨
📌 Important: candidates with an experience relevance of 85% or more are considered (outstaffing position).

🏢 About the project: a large retail chain. Development of an analytical platform and support of business processes using modern tools (BI, LLM, Data Contracts).

🧩 About the role: we are looking for a data analyst who is confident in SQL and Python, can build understandable dashboards, and is not afraid to use LLM to accelerate work processes. An excellent option for a specialist who wants to grow at the intersection of classical analytics and modern Data practices.

🚀 Key tasks: — Preparation of ad-hoc analytics and regular extracts in SQL and Python. — Creation of reports and interactive dashboards in Power BI or Apache Superset. — Control of the correctness of loaded data (DQ) and launching ready-made DAG processes. — Data reconciliation in Spark (filtering, JOIN, aggregations in DataFrame). — Maintaining and updating documentation in DataHub, working with code in GitLab. — Application of LLM models for analyzing texts, data, and code snippets.

🎯 Mandatory requirements (Hard Skills): — Data analytics experience at least 2 years. — Confident command of SQL: JOIN, CTE, aggregations, window functions, writing clean and structured code. — Skills in working with Python: pandas, numpy libraries, writing scripts for one-time analytics, visualization (plotly, seaborn). — Basic skills in Spark: executing simple queries and DataFrame operations. — Experience with BI tools (Power BI or Apache Superset), ability to build basic types of visualizations. — Understanding of the ETL process lifecycle and basic data quality assessment methods (DQ). — Ability to work with data contracts. — Practical experience in applying LLM: composing effective prompts, considering model limitations.

💡 Will be a significant plus: — Experience in the retail domain. — Basic understanding of dbt or other data transformation tools. — Experience in automating routine analytical tasks.

📲 Contact for application: recruiter contact (⚠️ DEADLINE: 10.27 until 17:00! When applying, please immediately send your updated resume with an emphasis on experience with SQL, Python, BI tools, and practical application of LLM in work tasks. Please provide the vacancy ID: 92459_SS)