Аналитик данных

Yalantis provides IT services and consulting, focusing on developing software solutions and building data-driven platforms for various business needs.

• Design, build, and maintain dbt models including incremental strategies, snapshots, schema design, macros, and lineage;
• Design, build, and optimize ELT pipelines across ClickHouse, Snowflake, and PostgreSQL;
• Lead and execute migrations from legacy systems to dbt-based models;
• Build validation frameworks comparing pipeline outputs across sources to guarantee parity and correctness;
• Build and monitor data orchestration with Apache Airflow;
• Develop and maintain data collection pipelines from third-party REST APIs including authorization, monitoring, retries, and caching;
• Ensure data quality through validation, error logging, observability, and consistency control;
• Use Metabase as the primary BI tool for visualizations and quality monitoring dashboards;
• Collaborate with analytics, AI/ML, and client-side stakeholders to deliver clean, verified, and accessible datasets.

• 4+ Years of experience as a Data Engineer or in a similar technical role;
• Deep knowledge of SQL including complex queries and performance optimization;
• Deep knowledge of dbt for building data models, macros, and lineage;
• Strong skills building pipelines with Airflow and solid grasp of orchestration concepts;
• Hands-on experience with ClickHouse, Snowflake, or PostgreSQL in production;
• 3+ Years of Python development experience with a focus on data processing and API integration;
• Experience with ELT processes including data collection, processing, storage, and quality assurance;
• Experience with BI tools such as Metabase, Superset, Tableau, or Quicksight;
• Strong Git workflow including branching, PR reviews, and conflict resolution;
• Experience with CI/CD for data pipelines;
• Comfort working with AI coding assistants as part of daily workflow;
• Nice to have: Hands-on experience tuning ClickHouse for analytical workloads, experience migrating from ETL to ELT architectures, practical experience with AWS (S3, IAM, CloudWatch), experience with AI-native data workflows or LLM-powered analytics, understanding of data governance principles and data access control.

• Professional growth opportunities including individual development plans, mentorship, and reimbursement for professional certifications;
• Access to professional courses in the Corporate Learning Management System;
• Tech community and knowledge-sharing events;
• Corporate library, book club, volunteering, and charity initiatives;
• Medical insurance and regular medical check-ups;
• Sport reimbursement and mental health support;
• Paid vacation and sick leave;
• Fully-equipped offices with top-notch equipment and access to the company store.