About this role
Business Overview
PMGTech is the horizontal technology platform within BlackRock’s Portfolio Management Group (PMG), integrating investment research with advanced engineering, AI, and alternative data to make technology a direct driver of alpha. It operates as one global team across three verticals – Platform Strategy, Research Solutions (DS&S), and Platform Change (IPT) – partnering closely with the BlackRock Aladdin ecosystem and PMG investment leadership. This integrated model delivers a coherent tech strategy, strengthens the research community, and scales capabilities across regions, asset classes (Equities, Fixed Income, Multi-asset), and investment styles (discretionary and systematic).
PMGTech leads PMG’s AI strategy by building an AI-ready research environment, unified data layer, agentic orchestration networks, and an investment-focused application layer to deploy AI-powered research solutions into production. As part of PMGTech, you will work directly with investment researchers and portfolio managers to build and scale capabilities in data engineering, GenAI, and platform tooling that streamlines research workflows and enables differentiated alpha-generative investment insights across PMG’s investment pillars.
Job Purpose / Background
The Research Engineer supports investors and research teams by building data workflows, research tools, analytics pipelines, and AI-assisted capabilities that help transform investor hypotheses into actionable insights. Embedded within DS&S research pods - asset-class focused sub-teams - this role requires collaboration with investors/researchers, AI Leads, and core engineering team to deliver high-quality data assets, exploratory analyses and research-enabling components.
This role requires that the engineer understand the business context and hypothesis of investors and translate the requirement into functional data solutions. This requires expertise in building and operating data intensive research solutions using Python and SQL, workflow orchestration, Cloud Big Data technologies such as BigQuery/Snowflake/GCS, visualization tools such as Tableau/Power BI and experience in data quality, CI/CD pipelines, and data operations.
Key Responsibilities
Build and maintain web harvesting and data pipelines, transformations, and workflows to support research hypotheses and data analyses.
Develop new 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.
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.
For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock
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.
