Lead Data Engineer, Portfolio Management Group, Associate

About this role About Global Fixed Income Team BlackRock’s active fixed income portfolio strategies stretch across a range of investment styles and segments of the fixed income universe. The breadth and depth of our platform puts us in a strong position to potentially deliver attractive returns in various market environments. With a focus on alpha generation and risk management, the team uses a top-down view from lead portfolio managers and bottom-up expertise from our sector specialists. Key Responsibilities Lead the design, development, and optimisation of scalable data pipelines and data platforms for structured and unstructured data Own end-to-end data engineering solutions, including ingestion, transformation, orchestration, storage, and serving layers for analytics and AI use cases Architect robust data models, pipeline frameworks, and reusable components that improve reliability, scalability, and maintainability Drive best practices for data engineering, including coding standards, testing, observability, performance tuning, and release processes Mentor junior engineers and provide technical leadership across design reviews, debugging, and delivery of complex data initiatives Collaborate with AI engineers, application developers, product managers, and business stakeholders to translate requirements into production-grade data solutions Design and implement data quality controls, validation frameworks, and monitoring mechanisms to ensure trusted downstream consumption Optimise data platforms and workloads for cost, scalability, resilience, and performance across cloud-based environments Partner with cross-functional teams to shape data architecture decisions and support delivery of enterprise-scale data products Education and Qualifications/Skills: Bachelor's or Master's degree in Computer Science/Engineering or related field. 5+ years of relevant experience. Good understanding of the foundations of data engineering Strong expertise in Python and SQL with hands-on experience building enterprise-grade data engineering solutions Deep experience with cloud data platforms such as Snowflake and modern data pipeline or orchestration frameworks Strong understanding of data modelling, ETL/ELT design, pipeline optimisation, and large-scale data processing patterns Experience designing reliable data quality, monitoring, lineage, and observability practices for production environments Experience with APIs, distributed systems concepts, and integration of data platforms with analytics or AI applications Strong knowledge of Git, code reviews, CI/CD practices, and software engineering standards for maintainable delivery Leadership & Problem-Solving Strong architectural thinking, problem-solving ability, and the capability to lead technical decisions, mentor team members, and drive delivery across complex data initiatives Our benefitsTo help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about. Our hybrid work model BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. Guidance on AI use for candidates At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self. About BlackRock At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.  Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress. This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive. To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok. BlackRock is proud to be an Equal Opportunity Employer.  We evaluate qualified applicants without regard to age, disability, family status, gender identity, race, religion, sex, sexual orientation and other protected attributes at law.