ID 3662. Data analyst

Requirements

• 2–4 years of experience in data analytics, analytics engineering, or data engineering.
• Strong expertise in writing complex, performant SQL for data transformation and analysis.
• Experience with dbt for data modeling.
• Looker Core (LookML) proficiency — experience building explores, model files, and views in the core Looker product
• Experience building and maintaining production-grade data models and transforming raw data into clean, actionable datasets.
• Ability to understand business metrics and translate stakeholder requirements into technical tasks.
• Experience working with stakeholders and communicating technical concepts to non-technical audiences.
• Comfortable working in a fast-paced environment and managing multiple priorities simultaneously.
• Must be able to work core hours aligned with EST (until 3:00 PM EST)

Nice to have

• Experience working with cloud data warehouses such as Snowflake.
• Experience with version control (e.g., GitHub) and CI/CD workflows.
• Experience implementing data quality tests.
• Experience with multiple BI tools (Looker + Tableau or Power BI) is preferred over deep specialization in a single tool
• Experience with AI/LLM tooling in data context (Snowflake Cortex, AI agents, conversational analytics).
• Familiarity with semantic layer concepts in dbt (dbt Semantic Layer / MetricFlow).

Brief description of the project:

We are looking for an Analytics Engineer to contribute to the transformation layer and help maintain high standards for reporting. You will sit at the intersection of Data Engineering and Data Analytics, transforming raw data into clean, well-modeled datasets. You will contribute to data modeling and architecture decisions, working closely with senior team members who will support your onboarding and growth. The team already has established processes and tools in place.

Краткое описание задач:

• Data Modeling: Design, develop, and maintain robust data models, with ownership of specific areas.
• Pipeline Excellence: Partner with Data Engineers to optimize ingestion and ensure the reliability of our data warehouse and query optimization.
• Business Partnership: Work with data analysts and stakeholders across the organization to translate complex business requirements into technical specifications.
• Code Quality: Contribute to version control, CI/CD practices, and data quality testing
• Documentation: Maintain a high-quality data dictionary to ensure everyone in the company speaks the same "data language."

Контакты:

https://t.me/annaromannaa

a.brazhnikova@agima.ru