Design, develop, test, deploy, and maintain production-grade data pipelines and reusable ingestion and transformation components for structured and semi-structured data.
Develop scalable data models and extract, load, and transform (ELT) transformations, using advanced SQL to support complex workloads while optimizing performance, scalability, and cost.
Develop and operate reliable directed acyclic graph-based workflow orchestration frameworks for data and batch processing while implementing automated data-quality checks, reconciliation, lineage, alerting, monitoring, and failure handling.
Build modular, maintainable, well-tested solutions and improve engineering productivity through reusable frameworks, automation, and responsibly governed artificial intelligence (AI)-assisted development.
Partner with product teams, data specialists, and consumers to translate requirements into dependable solutions, taking end-to-end ownership and communicating progress, risks, and issues.
Diagnose production issues and improve reliability, observability, and resilience while contributing to modernization and migration of existing data pipelines to BlackRock's enterprise data platform.
Your experience
Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience, with at least 4 years of hands-on experience building and supporting enterprise data pipelines, platforms, or data-intensive applications.
Strong Python development skills with experience in modular design, error handling, logging, automated testing, Git-based development, peer review, and continuous integration and continuous delivery practices.
Advanced SQL and strong hands-on Snowflake experience, including complex transformations, schema design, semi-structured data, ELT patterns, query troubleshooting, and performance and cost optimization.
Practical experience developing and troubleshooting data workflows, combined with a strong understanding of data warehousing and modeling concepts, including dimensional and historical data design.
Strong analytical, problem-solving, communication, and collaboration skills, with the ability to diagnose complex data and production issues and take ownership in an agile, globally distributed environment.
Experience with large-scale distributed data analytics engines and exposure to modern transformation, application programming interface (API), data-format, distributed event streaming and messaging, and Azure or Amazon Web Services (AWS) cloud technologies.
Experience with reusable data-engineering capabilities, governance and lineage, cloud or legacy modernization, financial or alternative data, and secure AI-assisted software development is beneficial.
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.
