Data Analyst

Description

About us:

Penlink is a global leader in digital intelligence solutions. Our advanced technologies simplify complex data, empowering public safety organizations to make informed decisions quickly and effectively. We believe in the power of data-driven intelligence to accelerate clarity in decision-making for global security, strategic operations, and the most critical missions. Headquartered in the US with offices worldwide.

About the Role:

We are seeking a talented and driven Data Analyst to join our data product team. This role combines analytical expertise, strong technical skills, and a deep understanding of large-scale datasets to support product development and business growth. As a Data Analyst, you will work closely with Product, Development, and Business teams to transform complex data into actionable insights and enable data-driven decision making.

Responsibilities 

• Lead and execute data analyses, data quality assessments, validation processes, and analytical investigations to provide actionable insights. 
• Analyze large-scale datasets to evaluate new data sources, identify trends, and uncover business opportunities.  
• Research, design, and validate data models and methodologies to support product and development teams, as well as customer needs. 
• Develop, maintain, and improve dashboards, reports, and monitoring tools for tracking key business and product metrics.  
• Present findings and recommendations to both technical and non-technical stakeholders.  

Requirements

• At least 2 years of experience as a Data Analyst, Product Analyst, or similar role. 
• Strong SQL proficiency.
• Experience with Python for data analysis and automation.  
• Experience working with large-scale datasets and analytical investigations.  
• Fluent in English.

Advantages

• Experience with Geospatial, Location Intelligence, or Cyber data.  
• Experience with AWS services, particularly Athena.
• Experience working with Datadog, Apache Spark, or Power BI. 
• Experience using AI tools for data analysis, research, and productivity enhancement.