Project
Raft AI4BI is a platform that combines BI, DWH, and AI analytics. Users can ask questions about data in natural language, receive analytics, and visualizations.
The product is already used by major clients in retail, finance, manufacturing, and other industries.
Who We Are Looking For
Someone who takes the implementation of AI4BI at the client's site from a signed contract to actual operation — and does it with their own hands, not by assigning tasks to a large team.
In the project team, you will work with a developer and a DevOps engineer; an architect will be involved on a case-by-case basis when something fundamentally new needs to be built. There is no analyst in the team: investigation, data model, technical specification, data marts, acceptance testing — this is your area. The developer handles implementation, and DevOps handles the environment and deployment.
The second half of the role is account development. You are the first to see where the client is still struggling: which department lacks analytics, which data source is not connected, which process would benefit from a dashboard. You formulate this as the next phase of work and bring it for estimation.
What You Will Be Doing
- Investigating the client's landscape: data sources, data quality, access, integration environment.
- Designing the analytical solution: ER models, grain and structure of data marts, semantic layer.
- Writing technical specifications and integration specifications.
- Designing loading pipelines: REST/SOAP API, ETL/ELT, streaming delivery via Kafka/RabbitMQ.
- Managing the project: scope, deadlines, risks, statuses, communication with the client from analyst to director.
- Collecting and verifying data independently — SQL and Python where it's faster to do than to describe.
- Conducting demos, UAT, user training, handing over the project to support.
- Formulating and justifying tasks for the architect when a new solution is required.
- Maintaining the account map and initiating expansions: new domains, new integrations, rollouts to adjacent departments.
What Is Important to Us
Mandatory:
- Proficient SQL skills — window functions, CTEs, query plan analysis, optimization. We will test this with a live task during the interview; it's a key skill for the role.
- Experience managing implementation projects from start to finish with a small team (2–4 people), where you handled system analysis and task definition yourself.
- System analysis with a focus on data modeling — normalized and star schemas, SCD, conscious choice of data mart grain, ER diagrams.
- Experience designing analytical solutions and integrations — REST/SOAP API, ETL/ELT pipelines, loading from multiple heterogeneous sources.
- Python for data manipulation — pandas, requests: parsing API responses, performing transformations, checking export quality.
- AI tools in daily work — including at the level of quickly coding PoCs/prototypes yourself to show the client — Claude Code, Cursor, Codex.
- Understanding of message brokers (Kafka/RabbitMQ) — when they are needed, how to describe an event contract. Implementation is done by the developer.
Will be a plus:
- Apache Superset: datasets, semantic layer, dashboards, access control.
- Knowledge of procurement and/or sales domains — significantly speeds up project startup.
- Experience with data scraping.
- Understanding of CI/CD processes.
How the Selection Process Works
- Interview with a recruiter.
- Test task (you will need to code the solution).
- Technical interview — discussion of the test task + live SQL tasks, data manipulation, modeling, and system analysis.
- Final interview — project management, communication with clients and team.
Conditions
- Work with real AI/BI solution implementations and major clients.
- Opportunity to influence the entire project — from investigation and design to implementation and further client development.
- A team of strong technical specialists and the opportunity to quickly grow in AI and data work.
- Full-time employment with flexible hours.
- Salary up to 200,000 rubles gross
