• Design, implement, and maintain scalable and reliable data infrastructure in GCP. • Build and optimize data pipelines fed by blockchain indexers to support our blockchain explorer, API, and analytics. • Design data models that effectively handle the unique privacy and cryptographic constraints of Aleo’s zero-knowledge network architecture. • Own, develop, and optimize APIs that serve data directly to our mobile privacy wallets and external products. • Manage and optimize database technologies, with a focus on Postgres and BigQuery. • Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting. • Collaborate with product and engineering teams to understand requirements and deliver high-performance APIs. • Identify opportunities to optimize the performance and cost of data platforms. • Utilize infrastructure-as-code (Terraform and Helm) to deploy and manage data environments. • Help define the technical vision and evolution of our data platform and architecture.

• Design, build, and maintain data platforms and pipelines supporting analytics, data science, BI, and AI. • Lead the evolution of Jellyfish’s Databricks Lakehouse platform. • Enable enterprise-wide agentic analytics within Databricks with trusted datasets. • Help mature core Databricks platform capabilities including Unity Catalog and platform observability. • Build and maintain ingestion pipelines for high-value data. • Partner on data flows sending trusted data to other internal systems. • Collaborate with stakeholders to understand analytical needs and design platform solutions. • Create standards and reusable patterns for data modeling, documentation, testing, and governance. • Develop tools and processes to monitor data platform health, pipeline reliability, cost, performance, and usage. • Provide technical leadership as a senior individual contributor.

• Designing and operating always-on product environments for customer demos, internal use, and stakeholder access • Building feature branch / preview environments to support UX and rapid feedback loops • Enabling internal dogfooding through real, long-running deployments of UDS products • Integrating core system components across Fleet Management, Edge Management, OS, and related services • Reducing reliance on local environments by creating shared, reproducible infrastructure • Supporting pathways toward self-service demo and trial environments • Improve system reliability by enabling continuous, real-world usage and validation • Partnering with engineering, product, and UX to ensure environments reflect real user scenarios

• Own client workstreams independently • Co-lead automation initiatives • Evolve the organisation's automation practice • Deliver high-quality automation solutions across multiple projects • Operate independently in client-facing roles