About this role
Job title: Research Engineer
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
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Build and maintain web harvesting and data pipelines, transformations, and workflows to support research hypotheses and data analyses.
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Develop new platform capabilities to source high-quality data and create scalable and maintainable data solutions.
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Develop research utilities, prototypes, dashboards, or exploratory tools as needed by the pod for insight generation or research workflows.
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Engage with investors and researchers to understand research workflows and translate requirements into data solutions.
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Collaborate with core engineering teams to adopt data extraction and management tools and technologies to accelerate investor research.
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Collaborate with AI leads to source data and build AI applications to supplement investor research with AI-assisted solutions.
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Skills & Experience
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Strong programming skills in Python and SQL.
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Strong problem-solving and analytical skills
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Knowledge/curiosity about investment research workflows or similar domains.
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Prior experience in data engineering or data analytics