Analytics Engineer
EUR 31,200-57,600 per year
Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 3
Grafana @ 1
Python @ 6
SQL @ 1
Looker @ 1
dbt @ 1
ETL @ 3
Airflow @ 1
Communication @ 3
Git @ 3
Data Analysis @ 3
API @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The world’s most advanced VPN, and a whole lot more.
If you’re a curious problem-solver who carves their own path, join the team behind Threat Protection Pro, the NordLynx protocol, and the fastest VPN on the planet—tools that put privacy, security, and control back in people’s hands.
Your impact: Helping millions take back control of their online security, privacy, and data.
Responsibilities
- Acquire data from various data sources (APIs, relational and non-relational databases, queues, etc.) by developing scripts, workflows, and ETL pipelines
- Support ETL processes and data transformations to address stakeholder requests
- Maintain existing data models’ integrity and structure on the data warehouse
- Use GitLab for version control, managing branches, creating merge requests, and conducting peer code reviews
- Monitor and analyze pipeline performance and data accuracy
- Participate in code reviews and write unit tests to ensure high-quality solutions
- Ensure all pipelines and processes comply with internal guidelines and requirements
- Closely work with the data analytics team to help automate repetitive tasks, improve efficiency and consistency, and create ad-hoc datasets
- Discover opportunities for data acquisition, diagnostics, mapping, and correction
- Recommend and validate ways to improve data reliability, efficiency, and quality
- Collaborate with cross-functional teams to ensure accurate understanding of data and business processes
Requirements
- Advanced proficiency in Python; experience with PySpark
- Basic knowledge of interacting with APIs (API requests)
- Familiarity with MinIO or similar environments for large-scale data workloads
- Comfortable working with GitLab (creating branches, committing code, creating merge requests, code reviews)
- Understanding of Git workflows and best practices
- Hands-on experience with unit testing and code reviewing
- Experience with Apache Airflow (creating and maintaining data pipelines) or familiarity with other orchestration tools is a plus
- Passion for data analysis with a focus on data quality
- Experience creating dashboards in tools like Looker or Grafana is a plus
- Proficiency in SQL; experience with BigQuery and dbt is a plus
- Knowledge of OpenSearch is a plus
- Ability to critically assess incoming requests, clarify requirements, and define a clear execution roadmap
- Excellent communication skills, problem-solving abilities, and a collaborative mindset
Tools You Will Use
- Python & PySpark
- Apache Airflow
- GitLab
- Looker & Grafana
Salary
- Monthly gross salary: 2600 - 4800 EUR