Analytics Engineer

Team: Data Infrastructure & Analytics

Reporting to: VP of Data Infrastructure & Analytics

Location: Berlin, Warsaw, Cracow

About Volt:

Volt is revolutionising how people pay online, globally. Our technology frees consumers from cards by letting them ‘Pay by Bank’. It’s effortless. It’s lightning fast. It’s the future. For businesses everywhere, it’s transformative.

We’re already trusted by leading brands around the world, but the real-time revolution is only just beginning. Having raised $83.5m, we’re accelerating our mission of delivering real-time payments, everywhere. And that’s where you come in.

We need world-class talent to create a world where consumers pay, and businesses get paid, instantly. With headquarters in London and offices in Amsterdam, Berlin, Kraków and Warsaw – and an all-star team already in place – we’re sure you’ll fit right in.

About the role:

As an Analytics Engineer, you will be one of the driving forces behind designing and maintaining the infrastructure that supports data analysis and reporting within our organization. Your expertise in statistical methods, data analysis best practices, and data visualization will enable you to translate complex data insights into easily understandable information for non-technical stakeholders. You will play a key role in designing data models and architectures, developing insightful reports and visualizations, and collaborating with cross-functional teams to provide data-driven insights and recommendations. Your meticulous attention to data accuracy and integrity, combined with your commitment to staying current with the latest data technologies and best practices, will be instrumental in optimizing our data analysis processes and delivering valuable insights to drive strategic decision-making.

What the role involves:

• Data Model and Architecture Design:

• Collaborate with data scientists, analysts, and other stakeholders to design and implement data models and architectures that support analytics and reporting.
• Ensure data structures are optimized for efficient data analysis and storage.

• Reporting and Visualization Development:

• Develop and maintain insightful reports, interactive dashboards, and data visualizations that effectively communicate data insights to stakeholders.
• Employ data visualization tools (e.g., Tableau, Power BI, Looker) to present complex data in a clear and intuitive manner.

• Data-Driven Decision Support:

• Work closely with cross-functional teams to understand business requirements and translate them into actionable data insights and recommendations.
• Provide analytical support and expertise to stakeholders, empowering evidence-based decision-making.

• Data Validation and Cleaning:

• Implement data validation and cleaning processes to ensure data accuracy, consistency, and integrity.
• Identify and address data quality issues to improve the reliability of analytical outputs.

• Technology and Best Practices:

• Stay up-to-date with the latest data technologies, statistical methods, and data analysis best practices.
• Continuously improve data analysis processes and methodologies to enhance efficiency and effectiveness.