• Participate in the development and maintenance of data pipelines in Python • Support the use of Databricks for data processing and transformation • Contribute to the implementation of orchestration workflows with Airflow or Prefect • Assist with data integration in cloud environments (AWS) • Collaborate with the data team on projects focused on performance and scalability

• Design and implement end-to-end data solutions on Microsoft Azure • Develop scalable and efficient data architectures that support large-scale data processing and analytics workloads • Ensure high performance, security, and compliance within Azure data solutions • Work closely with business and technical teams to understand and translate data needs into robust, scalable data architecture solutions • Provide expertise and leadership to the development team implementing data engineering solutions • Collaborate with Data Scientists, Analysts, and other stakeholders to ensure data architectures align with business goals and data analysis requirements

• Define and own the target data architecture and migration strategy for moving data infrastructure from AWS to Azure • Design end-to-end cloud-native data architectures leveraging Azure services, Snowflake, Databricks, and modern ETL/ELT and orchestration frameworks • Establish architectural principles, standards, and reference architectures covering: Data ingestion, transformation, and orchestration, analytical and research data platforms, security, access control, and compliance, scalability, performance, and cost optimization • Lead architectural decision-making across batch and streaming data pipelines, supporting both operational and research workloads • Partner closely with data engineers, analytics teams, and investment stakeholders to ensure architecture aligns with business and research needs • Guide and review solution designs, ensuring adherence to architectural standards and best practices • Define approaches for data modeling, metadata management, lineage, and data quality across the platform • Support integration of financial and market data providers (e.g., Bloomberg, LSEG, MSCI, FactSet) into the target architecture • Act as a trusted technical advisor to senior client stakeholders, translating complex technical concepts into clear architectural guidance • Engage directly with C-level executives and senior leadership to shape data strategy, investment in platforms, and long-term architectural direction • Lead executive-level architecture discussions and design reviews, presenting trade-offs, risks, costs, and benefits to support informed decision-making • Translate business, investment, and research objectives into clear data architecture strategies, ensuring alignment between executive priorities and technical execution • Serve as a senior architectural voice in governance forums, influencing platform roadmaps, cloud strategy, and data operating models • Contribute to delivery planning, risk management, and governance within Agile and change programs • Mentor engineers and architects, promoting architectural consistency and engineering excellence

• Own the systems that discover, acquire, and transform unstructured content into clean, structured, queryable data • Build automated content discovery from the web • Design LLM-powered extraction pipelines • Build evaluation harnesses and optimize for cost at scale • Maintain data quality and serve downstream consumers