Offer summary

Qualifications:

4+ years of experience in analytics/data engineering roles, preferably in a B2B SaaS context., Deep knowledge of SQL and data normalization best practices., Hands-on experience with Airflow, dbt, and Snowflake., Excellent communication skills and a proactive problem-solving mindset..

Key responsibilities:

Partner with various teams to define and implement accessible data models.

Transform raw data into clean, analytics-ready models using dbt.

Ensure data consistency and integrity across multiple systems.

Collaborate on designing self-serve Looker experiences and debug data issues.

Job description

We’re a newly formed data & analytics team of three. Together, we’ve successfully built the foundation of our modern data platform using Airflow, Snowflake, and Looker. We're actively cleaning, aligning, and integrating multiple data sources — including marketing, finance, and product usage data — into a centralized and governed system.

We’re looking for a Senior Data Analytics Engineer to help us transform fragmented data sources into robust, scalable pipelines and analytical assets that support self-serve reporting and advanced analysis across our product and go-to-market teams.

As our Data Analytics Engineer you will be responsible for:

Partner with Analysts, Marketing, Product, and Finance teams to define and implement data models that make insights easily accessible.
Transform raw data into clean, governed, analytics-ready models using dbt.
Ensure data consistency and integrity across systems.
Collaborate on designing self-serve Looker experiences while optimizing performance and reducing manual reporting overhead.
Debug data issues across multiple source systems and orchestrate efficient resolutions.

Our Current Stack:

Data Sources: PostgreSQL, ClickHouse, HubSpot, Chargebee, QuickBooks, Zendesk, PostHog
ETL/ELT: Airflow, dbt, Python, custom connectors
Data Warehouse: Snowflake
Orchestration: Airflow
BI & Governance: Looker, OpenMetadata
Version Control: GitLab

Requirements

To be successful in this role you should have:

4+ years of experience in analytics/data engineering roles, ideally in a B2B SaaS or enterprise context
Deep knowledge of SQL, data normalization, and transformation best practices
Familiarity with data governance, Looker modeling (LookML)
A strong commitment to data quality and accuracy
Hands-on experience with Airflow, dbt, Snowflake
A proactive, problem-solving mindset with attention to data accuracy and maintainability
Excellent communication skills

Benefits

What's in it for you?

A focus on professional development
Interesting and challenging projects
Fully remote work with flexible working hours, that allows you to schedule your day and work from any location worldwide
Paid 24 days of vacation per year, 10 days of national holidays, and unlimited sick leaves
Compensation for private medical insurance
Co-working and gym/sports reimbursement
Budget for education
The opportunity to receive a reward for the most innovative idea that the company can patent

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