Analytics Engineer

Eleving Group; Warszawa; On-site; PLN 180,000 - 260,000; Full time

Job summary

Eleving Group is seeking an Analytics Engineer to join the Data Platform team in Warsaw, building a trusted, scalable analytical layer on top of Snowflake. You’ll craft analytics-ready data models and data marts, translating business needs into reusable data products for self-service analytics and Data Science.

You will work with Snowflake, dbt, SQL, Git, Python, and BI tools like Power BI and Redash, ensuring production-grade data pipelines and clear data lineage.

Qualifications

• Experience with Snowflake or another modern cloud data warehouse.
• Strong understanding of analytical and dimensional data modelling.
• Practical knowledge of dbt.
• Working knowledge of Git and Git-based development workflows.
• Experience with ELT/ETL and complex data transformations.
• Understanding of data-quality testing, documentation and lineage.
• Basic Python knowledge.
• Strong analytical and problem-solving skills.
• Ability to translate complex business processes into data models.

Responsibilities

• Design and maintain analytics-ready data models in Snowflake.
• Build and maintain transformations using dbt.
• Develop reusable fact tables, dimensions, intermediate models and data marts.
• Translate business requirements into scalable data models.
• Establish definitions for key metrics and KPIs.
• Build automated data-quality tests and validation checks.
• Create certified datasets for Power BI, Excel, Redash and Data Science.
• Replace repetitive manual/Excel-based transformations with reusable Data Platform solutions.
• Document models, business definitions and data lineage.
• Collaborate with Data Engineers, Data Scientists, analysts and stakeholders.
• Treat analytical models as production code with Git, reviews, testing, and controlled deployments.

Skills

Snowflake

dbt

SQL

Git

Data modelling

ELT/ETL

Data quality testing

Python (basic)

Analytical thinking

Tools

Snowflake

dbt

SQL

Git

Power BI

Redash

Python

Job description

We’re looking for an Analytics Engineer to join our Data Platform team and help us build a trusted, scalable analytical layer on top of Snowflake.

This role sits at the intersection of Data Engineering, Data Science, BI, and Business. Your main responsibility will be turning raw and source-system data into reliable, well-structured and reusable business data models and data marts.

What you’ll do:

• Design and maintain analytics-ready data models in Snowflake
• Build and maintain transformations using dbt
• Develop reusable fact tables, dimensions, intermediate models and data marts
• Translate business processes and requirements into scalable data models
• Establish consistent definitions for key business metrics and KPIs
• Build automated data-quality tests and validation checks
• Create certified datasets for Power BI, Excel, Redash and Data Science
• Replace repetitive manual/Excel-based transformations with reusable Data Platform solutions
• Document models, business definitions and data lineage
• Work closely with Data Engineers, Data Scientists, analysts and business stakeholders
• Treat analytical models as production code using Git, code reviews, testing and controlled deployments

Our core stack:

Snowflake | dbt | SQL | Git | Python | Power BI | Redash

What we’re looking for:

• Practical experience with Snowflake or another modern cloud data warehouse
• Strong understanding of analytical and dimensional data modelling
• Practical knowledge of dbt
• Working knowledge of Git and Git-based development workflows
• Experience with ELT/ETL and complex data transformations
• Understanding of data-quality testing, documentation and lineage
• Basic Python knowledge
• Strong analytical and problem-solving skills
• Ability to understand complex business processes and translate them into data models

Why this role matters:

Our goal is to build a single source of truth for important business concepts and metrics.

You’ll help create the layer that turns technically available data into trusted, documented and reusable business data products — enabling faster analytics, better self-service BI and reliable datasets for Data Science.

If you enjoy combining data engineering practices with business understanding and analytics, we’d like to hear from you.