Nord Security
Technology
AnalyticsEngineer|Mid
Neural analysis suggests this role is
optimal for Mid candidates.
“Analytics Engineer | Mid at Nord Security. Skills: Data Engineering, ETL, Python, SQL. Acquire data from sources. Develop scripts and pipelines”
Industry & Context.
Problem-solving abilities
What They're Looking For.
Must Have
Advanced Python proficiency, Experience with PySpark, Basic API interaction, GitLab experience, Git workflows understanding, Unit testing experience, Code reviewing experience, SQL proficiency
Nice to Have
Familiarity with MinIO, Apache Airflow experience, Looker dashboard experience, Grafana dashboard experience, BigQuery experience, Dbt experience, OpenSearch knowledge
What You'll Do.
Acquire data from sources
Develop scripts and pipelines
Support ETL processes
Transform data for requests
Monitor pipeline performance
Analyze data accuracy
Participate in code reviews
Ensure guideline compliance
Automate repetitive tasks
Improve efficiency and consistency
Create ad-hoc datasets
Discover data acquisition opportunities
Recommend data reliability improvements
Validate data quality improvements
Collaborate with cross-functional teams
Ensure accurate data understanding
Ensure business process understanding
How You'll Work.
Team & Collaboration
Cross-functional teams; Data analytics team
Communication Scope
Clarify requirements
Process & Methodology
Roadmap definition
Full Job Description
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. MAIN RESPONSIBILITIES - Acquire data from various data sources (APIs, relational and non-relational databases, queues …) 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 writing unit tests to ensure high-quality solutions - Ensure all pipelines and processes comply with internal guidelines and requirements - Closely work with data analytics team to help them automate repetitive tasks, improve efficiency and consistency, also create ad-hoc datasets - Discover opportunities for data acquisition, diagnostics, mapping, and correction - Recommend and validate different ways to improve data reliability, efficiency, and quality - Collaborate closely with cross-functional teams to ensure accurate understanding of data and business processes CORE 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)
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