Vice President - Data Engineering, Aladdin Data

About this role The BlackRock Data Office (BDO) is responsible for building and advancing the firm's enterprise data capabilities by delivering trusted, scalable, and governed data products that power investment, business, operational, and technology outcomes across BlackRock. As a Data Engineer, you will play a key role in designing, building, and optimizing modern data platforms and pipelines that enable high-quality, reliable, and accessible data across the organization. You will partner closely with product managers, data stewards, platform engineers, software engineers, data scientists, and business stakeholders to develop reusable data capabilities that support analytics, reporting, machine learning, artificial intelligence, and digital products. Depending on experience and level, you will either contribute to or lead the design and implementation of complex data engineering solutions, influence technical direction, and help establish engineering best practices across the organization. The ideal candidate is passionate about solving complex data challenges, enjoys building scalable distributed systems, and is highly motivated to create, optimize, or redesign data pipelines to support our next generation of products and data initiatives. Given the highly execution-focused nature of the work, the ideal candidate will roll up their sleeves to ensure that their projects meet deadlines and will always look for ways to optimize processes in future cycles. Core Skills: Demonstrated ability to join a complex global team, collaborate cross functionally (data stewards, data scientists, platform engineers, business stakeholders), and take ownership of major components of the data platform ecosystem and develop data ready tools to support their job. Top technical / programming skills – Python, Java and Scala with ability to work across big data frameworks such as Spark, PySpark, Hive, Cloud Data Platforms Preferably Snowflake and SQL. Experience working with flat files (e.g., csv, tsv, Excel), Database API sources is a must to both ingest and create transformations. Primary Responsibilities: Design, develop, and maintain scalable, reliable, and high-performance data pipelines supporting enterprise data products. Build and optimize batch and real-time data ingestion, transformation, and publishing processes across diverse data sources. Develop reusable data engineering frameworks, components, and automation to improve platform efficiency and developer productivity. Ensure data products meet enterprise standards for quality, security, governance, lineage, and observability. Keep data separated and segregated according to relevant data policies. Identify opportunities to improve performance, scalability, resiliency, and cost optimization across the data platform. Troubleshoot complex production issues, perform root cause analysis, and implement sustainable long-term solutions. Contribute to engineering standards, code reviews, testing practices, CI/CD automation, and technical documentation. Automate manual ingest processes and optimize data delivery subject to service level agreements; work with infrastructure on re-design for greater scalability. Stay current on emerging technologies and recommend innovative approaches that improve the firm's data ecosystem. Associate: Deliver high-quality engineering solutions while continuing to deepen technical expertise across modern data technologies. Vice President: Provide technical leadership for complex initiatives, mentor junior engineers, influence architecture decisions, and drive engineering best practices across multiple teams. Qualifications: 7+ years of experience designing, building, and delivering enterprise-scale data engineering solutions, including demonstrated technical leadership responsibilities. 4+ years of strong Java, Python or Scala programming skills (Core Python and PySpark) including hands-on experience creating and supporting UDFs and modules like pytest. 4+ years of experience with building and optimizing ‘big data’ pipelines, architectures, and data sets. Familiarity with data pipeline and workflow management tools (e.g., Airflow, DBT, Kafka). 4+ years of hands-on experience on developing on Spark in a production environment. Expertise on parallel execution, deciding resources and different modes of executing jobs is required. 4+ years of experience using Hive (on Spark), Yarn (logs, DAG flow diagrams), Sqoop. Proficiency bucketing, partitioning, tuning and handling different file formats (ORC, PARQUET & AVRO). 4+ years of experience using Transact SQL (e.g., MS SQ Server, MySQL), No-SQL and GraphQL. Strong experience implementing solutions on Snowflake Experience with data quality and validation frameworks, especially Great Expectations for automated testing. Strong understanding and use of Swagger/OpenAPI for designing, documenting, and testing RESTful APIs. Experience in deployment, maintenance, and administration tasks related to Cloud (AWS, Azure Preferred), OpenStack, Docker, Kafka and Kubernetes. Familiarity with CI/CD pipelines for data pipeline automation and deployment (Jenkins, GitLab CI, Azure DevOps) Experience with data governance, metadata management, and data lineage using tools like Axon and Unity Catalog . Expertise in managing business glossaries, data access control, auditing, and ensuring centralized governance across data assets in both cloud and hybrid environments. Hands-on experience with Databricks, including notebooks, workflows, and ML integrations. Experience working across global, cross-functional teams in a collaborative and fast-paced engineering environment. Exposure to machine learning, artificial intelligence, or Generative AI technologies and the engineering patterns that support AI-ready data platforms is a plus. 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.