Research Engineer, Portfolio Management Group, Associate

About this role

Business Overview

Portfolio Management Group (PMG) Tech is the horizontal technology platform within BlackRock’s Portfolio Management Group (PMG), integrating portfolio management, risk management, and quantitative workflows with advanced engineering, AI, and data capabilities to make technology a strategic driver of investment and risk outcomes.

Risk & Quantitative Analysis (RQA) provides independent oversight of BlackRock’s investment and enterprise risks through quantitative analysis, risk expertise, and evidence-based insights. In partnership with PMG Tech, RQA leverages advanced engineering, AI, and data platforms to strengthen risk management capabilities, enhance decision-making, and scale innovative solutions across investment, operational, technology, and enterprise risk domains.

Job Purpose / Background

The Research Engineer partners with Risk & Quantitative Analysis (RQA), PMG Tech, and business stakeholders to build data workflows, analytics solutions, and AI-assisted capabilities that transform risk and quantitative challenges into actionable insights. Embedded within PMG Tech Pods—business-focused cross-functional teams—you will collaborate with risk managers, quantitative analysts, AI Leads, and engineers to deliver high-quality data assets, analytical tools, and technology solutions that support risk management and decision-making.

This role requires a strong understanding of business problems and risk workflows, with the ability to translate requirements into scalable data solutions. You will leverage Python, SQL, workflow orchestration, cloud data platforms (BigQuery, Snowflake, GCS), and visualization tools such as Tableau and Power BI to build and operate data-intensive applications. The role also requires experience with data quality, CI/CD pipelines, and data operations to ensure reliable, production-grade solutions that meet business needs.

Key Responsibilities

• Build and maintain web harvesting and data pipelines, transformations, and workflows to support research hypotheses and data analyses.

• Develop new platform capabilities to source high-quality data and create scalable and maintainable data solutions.

• Develop research utilities, prototypes, dashboards, or exploratory tools as needed by the pod for insight generation or research workflows.

• Engage with investors and researchers to understand research workflows and translate requirements into data solutions.

• Collaborate with core engineering teams to adopt data extraction and management tools and technologies to accelerate investor research.

• Collaborate with AI leads to source data and build AI applications to supplement investor research with AI-assisted solutions.

Skills & Experience

• Strong programming skills in Python and SQL.

• Strong problem-solving and analytical skills

• Knowledge/curiosity about investment research workflows or similar domains.

• Prior experience in data engineering or data analytics, or data intensive applications.

• Proven ability to work collaboratively across engineering and business teams.

Qualifications

• 3+ years hands-on experience in Data Engineering/Analytics

• B.S. / M.S. college degree in Computer Science, Data Science/Engineering, or related subject area.

Nice to Have

• Prior experience web harvesting tools and techniques (Scrapy)

• Experience with cloud data tools (Snowflake, BigQuery, GCP).

• Exposure to AI/ML tooling, LLM experimentation, or AI applications such as RAG, Summarization and Q&A (Open AI, Vertex, Anthropic).

• Experience creating dashboards, notebooks, or lightweight research tools (Streamlit, Flask, Tableau, Power BI).

• Familiarity with workflow orchestration or automation tools (Kubernetes/Airflow).

Our benefits

To 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.