• Develop and maintain scalable, secure, and efficient data architectures using Microsoft Fabric and Azure services, optimised for large data volumes and real-time analytics • Design and manage Azure cloud infrastructure, ensuring optimal performance, security, and cost-efficiency across Fabric workloads • Implement data integration solutions using Microsoft Fabric Data Factory, Synapse Pipelines, Logic Apps, and other Azure-native tools • Oversee the design, implementation, and maintenance of databases using Azure SQL, Lakehouse architecture in OneLake, and Synapse SQL Pools • Establish and enforce data governance policies using Microsoft Purview and Fabric’s built-in governance features • Monitor and optimise Fabric-based data systems for performance, scalability, and reliability • Ensure data solutions comply with enterprise security standards and regulatory requirements • Collaborate with development teams to build end-to-end data solutions, integrating Power BI dashboards, Fabric Notebooks, and backend services (.NET, C#, JavaScript) • Provide technical guidance and mentorship to Application Architects, Technical Leads, and Developers • Collaborate with distributed teams (onshore/offshore) and business stakeholders across 6–7 countries to design a consistent, unified platform

• Design and build scalable data pipelines to ingest, process, and transform blockchain data, trading events, user activity, and market signals at high volume and low latency • Architect and maintain data infrastructure that powers real-time trading analytics, P&L calculations, leaderboards, market cap tracking, and liquidity monitoring across the platform • Own ETL/ELT processes that transform raw onchain data from multiple blockchains into clean, reliable, and performant datasets used by product, engineering, analytics, and ML teams • Build and optimize data models and schemas that support both operational systems (serving live trading data) and analytical use cases (understanding market dynamics and user behavior) • Establish data quality frameworks including monitoring, alerting, testing, and validation to ensure pipeline reliability and data accuracy at scale • Collaborate with backend engineers to design event schemas, data contracts, and APIs that enable real-time data flow between systems • Partner with product and analytics teams to understand data needs and translate them into robust engineering solutions • Provide technical leadership by mentoring engineers, conducting code reviews, establishing best practices, and driving architectural decisions for the data platform • Optimize performance and costs of data infrastructure as we scale to handle exponentially growing trading volumes

• Collaborate with cross-functional teams to define data requirements, perform data collection, and ensure data quality and integrity. • Curate data sets including through hands on analyses and automated tools including web scraping, ETL pipelines and SQL queries. • Conduct in-depth research and analysis to identify new data sources and complement existing data sources. • Design and maintain intuitive BI dashboards, reports, and visualizations to effectively communicate complex data and insights. • Identify actionable business insights through analysis of data trends, patterns, and correlations. • Own documentation of data processes, schemas, and data sets • Build using best practices in security, design, and data quality.

• Design and develop ETL/ELT pipelines on platforms like Databricks (PySpark, Delta Lake, SQL), Informatica, Teradata, Snowflake • Architect data models (batch and streaming) for analytics, ML, and reporting • Optimize performance of large-scale distributed data processing jobs • Implement CI/CD pipelines for Databricks workflows using GitHub Actions, Azure DevOps, or similar • Build and maintain APIs, dashboards, or applications that consume processed data (full-stack aspect) • Collaborate with data scientists, analysts, and business stakeholders to deliver solutions • Ensure data quality, lineage, governance, and security compliance • Deploy solutions across cloud environments (Azure, AWS, or GCP)