About this role

Role Overview

Data and AI are central to our platform and competitive advantage. We are seeking a Senior Principal Data Engineer to design, build, and operate large‑scale, enterprise data platforms, with deep AI/ML and GenAI expertise—not only enabling AI use cases, but using AI as a first‑class tool to design, build, and optimize data pipelines.

This role is a hands‑on senior engineering position with architectural ownership, operating at the intersection of data engineering, AI/ML systems, and platform modernization.

Key Responsibilities

• Architect, build, deploy, and operate scalable ETL/ELT data pipelines supporting analytics, ML, and GenAI workloads.

• Use AI/ML and GenAI to design and build data pipelines, including: AI‑assisted pipeline and schema design; AI‑generated and optimized transformation logic and code; automated test generation, data validation, and performance tuning; AI‑driven documentation and operational runbooks.

• Apply AI/ML techniques to automate data engineering workflows, including ingestion, schema evolution, data quality checks, anomaly detection, and pipeline optimization.

• Build and maintain feature engineering pipelines, training datasets, and feedback loops for production ML and GenAI systems.

• Enable GenAI use cases, including unstructured data ingestion, retrieval pipelines (RAG), and governance‑aware AI data flows.

• Ensure enterprise standards for reliability, observability, lineage, security, and compliance across all data and AI pipelines.

• Partner with product, program, analytics, and AI teams in Agile delivery models to translate business needs into scalable AI‑enabled data solutions.

• Provide senior technical leadership through architecture reviews, mentoring, and setting data & AI engineering standards.

Required Qualifications

• 15+ years of experience owning and operating large‑scale data engineering platforms in production.

• Strong hands‑on expertise in Python and SQL, with deep experience on cloud data platforms (AWS, Azure, or GCP).

• Proven experience architecting distributed, high‑performance data systems.

• Demonstrated experience using AI/ML or GenAI to design, build, or optimize data pipelines (not just consuming AI outputs).

• Strong experience supporting ML/AI systems in production, including feature pipelines, data validation, monitoring, and retraining support.

• Solid understanding of data modeling, performance tuning, DevOps/CI‑CD, and Agile delivery.

• Excellent communication skills and ability to operate in fast‑paced, cross‑functional environments.

Preferred Skills

• Experience with GenAI/LLM ecosystems (e.g., RAG, vector data, prompt or model lifecycle support).

• Experience with microservices, APIs, and large‑scale analytics platforms.

• Prior experience leading or mentoring senior engineers (player‑coach model).

• Experience working in financial services or regulated environments.

Why This Role

This role goes beyond traditional data engineering. You will use AI to fundamentally change how data pipelines are designed, built, and operated, while delivering mission‑critical data and AI platforms at enterprise scale.

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.