We are looking for a Junior Data Engineer who is ready to dive into the existing analytics infrastructure: understand the code, optimize pipelines, fix bugs, and add new processes. The stack is already set up — ClickHouse, Airflow, API integrations, GitHub.
But the main thing is not just support. We are in the process of actively implementing AI solutions into business processes, and the team faces ambitious tasks of creating large products using LLM and RAG. You will have the opportunity to develop in this specific direction: participate in the design and integration of AI components, work with vector databases, build pipelines for feeding context into models.
Responsibilities:
- Support and development of ETL/ELT processes: Ensuring the smooth operation of existing data pipelines (ClickHouse, Airflow), fixing errors, and monitoring data quality.
- Working with data sources: Setting up and supporting integrations with external sources via API, as well as processing files received by email.
- Administration of analytics infrastructure: Working with databases (ClickHouse, PostgreSQL), optimizing queries and storage structure.
- Automation: Writing Python scripts to automate routine data loading and transformation tasks.
- Working with Git: Maintaining pipeline code in a version control system (GitHub), participating in code reviews.
- Participation in R&D projects: Active involvement in the creation and implementation of the company's new large-scale projects related to the integration of AI/LLM into business processes (under the guidance of senior colleagues).
Requirements:
- Higher education;
- Preferably additional education in a relevant field;
- Work experience: from 1 to 3 years of commercial development or administration in Data Engineering.
- Programming language: Solid knowledge of Python.
- Databases: Practical experience with ClickHouse (creating tables, optimization, working with ReplacingMergeTree) and PostgreSQL.
- Orchestration: Experience setting up DAGs in Apache Airflow.
- Integrations: Experience working with external REST APIs.
- Tools: Solid command of Git.
Will be an advantage (plus):
- Experience with LLM or AI frameworks (LangChain).
- Understanding of the RAG (Retrieval-Augmented Generation) concept.
- Attention to detail and accuracy in working with data;
- Initiative, ability to independently solve problems and suggest improvements;
- Analytical mindset;
- Systemic approach to decision-making;
- Ability to work in a team and interact with analysts;
- Prioritization skills and ability to manage multiple tasks in parallel;
- Responsibility for results.
Conditions:
- Flexible work schedule: 5/2, from 8:00 to 17:00 (or 9:00 to 18:00);
- Official employment according to the Labor Code of the Russian Federation;
- Work in a comfortable office, hybrid schedule or full remote is possible (Moscow time, UTC + 3).
- Friendly team
- Free parking available;
- Work location: Khimki, MTK GRAND 1, Butakovo St., 4.
