Oxylabs28d ago

Analytics Engineer

Vilnius · VilniusFull Timemid

Data ScienceData EngineerAnalytics EngineerDataData & AI

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Quick Summary

Overview

We're a team of 600+ professionals who develop cutting-edge web data gathering solutions for thousands of the world's best-known businesses, including Fortune 500 companies.

Technical Tools

Data ScienceData EngineerAnalytics EngineerDataData & AI

We're a team of 600+ professionals who develop cutting-edge web data gathering solutions for thousands of the world's best-known businesses, including Fortune 500 companies.

What’s in store for you:
As our Analytics Engineer, you will become a crucial partner to our Finance team, helping to define and maintain the global view of our company's metrics. You won't just be building data tables, you will participate in discussions with our financial analysts to drive crucial commercial decisions. In addition, you'll be diving into the technical challenges of automating the finance team’s workflows, including engineering solutions to handle API integrations, reverse ETL processes, and the monitoring of sensitive data pipelines.

This is an excellent opportunity to work with complex SQL logic, wrangle huge datasets (hundreds of TBs) and implement interesting automation projects.

Partner with financial analysts to define and maintain the global view of company metrics, actively participating in discussions to support crucial commercial decisions.

Push the limits of dbt by developing scalable data models and writing custom macros to handle complex business logic, ensuring our code remains DRY and efficient.

Build end-to-end automations (using Python, Airflow, or n8n) to handle API integrations and reverse ETL processes that sync data back to operational systems.

Manage financial data pipelines by implementing rigorous monitoring, data quality tests, and freshness standards to guarantee trust in the numbers.

dbt mastery. You are comfortable writing custom macros, packages, and optimizing project structures.

Proficiency in SQL (performance tuning, readability) and at least one programming language, ideally Python.

Knowledge of some DataOps practices and tools including version control systems (e.g., Git), Docker, and CI/CD.

Experience with cloud infrastructure (ideally Google Cloud).

High degree of ownership.

Ability to prototype solutions quickly.

Technical aptitude and comfort with engineering-related discussions.

Excellent at communicating in both written and spoken Lithuanian and English.

Nice to have:

Familiarity with workflow automation tools (e.g., n8n).

Experience with reverse ETL patterns or tools.

Background in finance, fintech, or ecommerce data domains.

Google Cloud Platform (Pub/Sub, GCS, BQ) for ingestion, storage and warehousing.

dbt and SQL for data modelling.

PowerBI and Superset for data visualisation.

Cursor/Claude Code for coding.

Airflow for orchestration.

n8n for automation.

Kubernetes/Argo CD for deployment.

Streamlit for data applications.

*We do not expect candidates to master or know all of the technologies today.

Gross salary: 3500 - 4800 EUR/month. Keep in mind that we are open to discuss a different salary based on your skills and competencies.

To support your professional growth and make you feel taken care of, we’ve put together an expansive benefit package. It covers learning, well-being, celebration, and much more — learn all about it here.