Senior Engineer, Public & Alternative Investments, Data Platforms

Our Public & Alternative Investments Data Platforms team integrates diverse vendor data sources, builds robust and scalable data pipelines, and delivers strategy-neutral, enriched, and centrally governed data products that empower investment decision-making and research across both Public Markets and Alternative Assets.

We also develop comprehensive carbon emissions datasets that help advance the Fund’s commitment to sustainable investing, enabling the integration of environmental insights into portfolio analysis and decision-making.

As a Senior Data Engineer, you will lead pieces of work focused on developing, constructing, testing, and maintaining Enterprise Data and large-scale processing systems. You will drive engineering excellence and continuous improvement within your team applying data engineering best practices to support the organization's data initiatives and contribute to the enhancement of Enterprise Data Products.

Accountabilities:

• Own aspects of designing, building, and maintaining scalable and efficient data pipelines to Data Products from various sources to storage and analytical systems.
• Provide on-call support for production systems, identify and create automation for reducing MTTR and mature operational runbooks.
• Help implement processes and tools to monitor and improve data quality, including data profiling, data freshness, and ensuring SLA adherence.
• Partner with Data Governance team to establish data governance policies and procedures to ensure data accuracy, privacy, and security.
• Advocate and drive adoption of DevOps & QE culture, supporting presentations in various internal forums and sessions on product releases, best practices, and provide consulting, guidance, and implementation assistance to users/application teams.
• Collaborate with cross-functional teams such as data scientists, analysts, and software engineers to understand data requirements and deliver solutions that meet business needs.
• Stay updated on emerging technologies, trends, and best practices in data engineering and related fields. Continuously evaluate and adopt new tools and techniques to enhance productivity and innovation.