• Design, build, and maintain analytical pipelines and reporting solutions on BigQuery and MariaDB • Write sophisticated, performant SQL to extract insights from large-scale datasets • Leverage AI and machine learning features to augment analytics workflows • Use AI-powered development tools to accelerate your workflow • Develop internal tooling and automation using Python, FastAPI, and modern frameworks • Communicate findings clearly to stakeholders • Understand and document data architecture • Collaborate on business process analysis • Proactively identify opportunities for improvements

• Design and maintain data models, implement robust testing, improve documentation, and manage CI/CD workflows. • Build and maintain the semantic layer that powers reporting, self-serve analytics, and downstream consumers (Mixpanel, Braze, internal tools). • Work closely with engineering, product, and commercial teams to translate business questions into reliable, well-modelled data. • Take ownership of data quality; monitoring, altering, and proactive fixes across the pipeline. • Help shape the next iteration of our data platform: think AI-native architecture, semantic APIs, and making our unique data assets (mod dependency graph, behavioural data at scale) actually usable. • Core stack: ClickHouse (warehouse), dbt (transformation), Mixpanel (product analytics), Braze (lifecycle marketing), with a growing AI/LLM layer on top.

Analytics Engineer Location: Remote, but within the UK. Salary: £40,000 - £50,000 Please note: We are unable to sponsor international visas at this time. About Nexus Mods Established in 2001, Nexus Mods is the largest video game modding platform on the internet - a household name in the PC gaming ecosystem. - 71M+ registered members - 800K+ mods for 4,000+ games - 21B+ mod downloads We’re currently focused on product modernisation, driving growth and building infrastructure for the next 10 years of community-powered modding. Our Role:  We’re looking for a hands-on Analytics Engineer to help us build and scale a modern data platform. This is a high impact role where you’ll own our analytics layer end to end, from raw data to trusted, business critical insights.  You’ll be joining as the second member of the data team, working directly with the Head of Data. This means high autonomy, fast decision making, and the opportunity to shape how data is used across the company from the ground up.  Responsibilities:  - Design and maintain data models, implement robust testing, improve documentation, and manage CI/CD workflows.  - Build and maintain the semantic layer that powers reporting, self-serve analytics, and downstream consumers (Mixpanel, Braze, internal tools). - Work closely with engineering, product, and commercial teams to translate business questions into reliable, well-modelled data.  - Take ownership of data quality; monitoring, altering, and proactive fixes across the pipeline.  - Help shape the next iteration of our data platform: think AI-native architecture, semantic APIs, and making our unique data assets (mod dependency graph, behavioural data at scale) actually usable.  - Core stack: ClickHouse (warehouse), dbt (transformation), Mixpanel (product analytics), Braze (lifecycle marketing), with a growing AI/LLM layer on top.

• Implement a comprehensive data strategy aligned with Digistore24’s goals. • Support the management of the entire data domain: architecture, technology decisions, policies, procedures, cost monitoring, alerting, etc. • Ensure the data foundation is performant and scalable to meet business needs. • Expand analytics capabilities and drive the development of predictive models and data visualization tools. • Communicate and align with various teams on business and technical requirements. • Work with clear goals and objectives to ensure alignment with organizational priorities. • Ensure the accuracy, reliability, and integrity of data analysis processes and results. • Implement best practices for data acquisition, integration, transformation, and delivery. • Stay informed about current technologies and trends in data engineering. • Act as a subject-matter expert on data analytics and engineering topics and provide support and guidance when needed.