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описание
🌍 Do you enjoy modeling data, improving data quality and helping teams make decisions based on numbers they can trust? As a Analytics Engineer at Ecommpay, you'll be the bridge between raw data and real business insight. You'll make sure that when two teams look at the same metric, they see the same number, and they understand exactly what it means. You'll bring structure, clarity and consistency to the way data is built and used across the company.
задачи
Design and develop the analytics data layer: model data marts (dimensional modeling, star schema) and define grain and business entities
Build and maintain data transformations in SQL and Python, orchestrated in Airflow
Develop the semantic layer in Looker (LookML) with a single definition for every metric and dimension
Implement data quality checks, including: tests, freshness, completeness monitoring and alerts
Document models, metrics and lineage
Work with business teams, analysts and data engineers to turn requirements into data models with agreed metric definitions
Use AI tools to speed up development, refactoring, testing and documentation
Prepare data and context for internal AI use cases, so LLM agents can work with reliable metrics and tables
требования
2 years of hands-on experience in analytics engineering or a similar data role
Strong SQL skills, including CTEs, window functions, query optimization and reading execution plans, ideally with Vertica, MySQL or MSSQL
Experience with analytical data modeling (Kimball, SCD, facts/dimensions)
Solid Python skills and the ability to write clean, maintainable code (modules, configs, reusable functions)
Experience with Airflow or similar tools (Dagster, Prefect, Luigi)
Experience with BI tools and an understanding of how the data model affects dashboards
Git, code review and basic Linux/Bash
Hands-on experience with AI coding assistants (Claude Code, Codex, Copilot, Cursor) and the ability to critically review generated code (logic, joins and grain)
Confidence in working with the business to define exactly what is being measured, and in asking questions when something is unclear
English at B1 level or higher
Будет плюсом: LookML or other semantic layers (dbt Semantic Layer, Cube); dbt or similar approaches (modular SQL models, tests, documentation as code); Data quality and observability tools (Great Expectations, Soda, Elementary); Setting up AI agents for your workflow, such as repository instructions (CLAUDE.md, AGENTS.md) and MCP connections to the warehouse or BI; Kafka or NoSQL (Elastic); Reading PHP code to understand source system logic
условия
Join a fast-growing global FinTech where your work has real impact.
Be part of a 500+ international team, collaborate across four offices, and solve challenges that are transforming the way people and businesses move money
Take ownership of your growth with access to our internal Academy, relevant training and courses, and financial support for external learning.
Build expertise that matters and create opportunities to take on new challenges as you grow
Work remotely or in a hybrid setup, depending on your location, with the flexibility and autonomy to find the way of working that brings out your best.
We trust our people to take ownership, make decisions, and deliver results
