Top Data & Analytics Jobs

Own and govern investment and risk analytics within BlackRock’s Aladdin Data platform, ensuring accuracy, completeness, scalability, and commercial value. Develop analytics solutions and proofs of concept, address complex quantitative and financial-market requirements, and coordinate with product, engineering, operations, and client teams. Apply expertise in private markets, risk models, portfolio returns, performance attribution, and whole-portfolio analytics, including integration of eFront and Preqin capabilities.

Leads BlackRock Investment Stewardship’s Data & Analytics team and manages three engineers. Oversees data engineering, research and reporting platforms, automation, AI-enabled workflows, ETL/ELT pipelines, Snowflake lake house implementations, data quality, and integrations with Aladdin and external vendors. Partners with technology and analytics teams to support stewardship research, voting, engagement, and client reporting operations.

Lead Preqin’s EMEA private markets data team, overseeing data acquisition, quality, coverage expansion, market engagement, and strategic execution. The role requires senior people leadership, commercial judgment, stakeholder relationship management, and deep private markets expertise. The leader will also drive data modernization and AI-enabled transformation, improve operational efficiency and scalability, and collaborate with Product, Technology, Commercial, and Data teams to deliver high-quality market intelligence to clients.

Provides technical leadership for enterprise-scale data platforms and defines target-state architecture, engineering standards, technology roadmaps, and governance practices. Leads distributed data, application, integration, and streaming platforms; improves scalability, reliability, security, performance, and developer productivity. Partners with business and technology stakeholders, mentors senior engineers, drives AI-enabled engineering adoption, and oversees delivery across cloud, hybrid, workflow orchestration, observability, and data operations environments.

Designs, develops, and supports enterprise data platforms using Python, SQL, Airflow, dbt, Snowflake, cloud technologies, and modern data architectures. Responsibilities include building scalable pipelines and reusable frameworks, implementing metadata, lineage, governance, quality, and observability capabilities, integrating Agentic AI, supporting production operations, improving performance and reliability, leading technology evaluations, and mentoring engineers. The role also contributes to Agile delivery, testing, deployments, documentation, demonstrations, and cross-functional platform modernization initiatives.

Own data integrity and reconciliation across Salesforce, Entity Master, and related platforms. Investigate discrepancies, duplicates, missing records, and synchronization failures affecting onboarding and client servicing. Perform root-cause analysis, develop reporting, document processes, and support automated data-quality initiatives. Partner with business, data operations, engineering, and IT teams to resolve systemic issues and improve workflows.

Prepare and maintain portfolio and fund-level performance reporting and risk metrics for liquid credit strategies. Produce monthly/quarterly/ad hoc client reports, respond to investor data requests, ensure data and process integrity, and coordinate with valuation, fund accounting, investor relations, compliance, and PMs. Support operational due diligence and new product servicing.

Conduct quantitative research and post-trade analytics for securities lending. Develop trading signals, models, algorithms, and automated workflows; own production model monitoring and governance; apply AI and machine learning; and collaborate with traders, researchers, technologists, investors, and risk managers to deliver scalable electronic trading solutions.

Lead end-to-end design and delivery of analytics solutions that extend the Aladdin platform. Build end-to-end analytical applications using Python, databases and AI; prototype solutions, partner with product and tech teams, influence senior stakeholders, mentor peers, and translate investment challenges into scalable tools for portfolio analysis, sales, and client engagement.

Leads technology, data, automation, analytics, and applied AI solutions supporting investment manager research across public and private markets. Translates business requirements into scalable production systems, develops applications and dashboards, improves data quality and governance, and prototypes AI/LLM capabilities. Partners with research, investment, data, technology, operations, and vendor stakeholders while managing complex initiatives, controls, priorities, and adoption.