Data Platform Engineer, AVP - Data, Cloud & Developer Experience

Blackstone is the world’s largest alternative asset manager. We seek to create positive economic impact and long-term value for our investors, the companies we invest in, and the communities in which we work. We do this by using extraordinary people and flexible capital to help companies solve problems. Our $1.1 trillion in assets under management include investment vehicles focused on private equity, real estate, public debt and equity, infrastructure, life sciences, growth equity, opportunistic, non-investment grade credit, real assets and secondary funds, all on a global basis. Further information is available at www.blackstone.com. Follow @blackstone on LinkedIn, X, and Instagram.

Business Unit Overview:

Blackstone Technology & Innovations (BXTI) is the technology team at the core of each of Blackstone’s businesses and new growth initiatives. Serving both internal and external clients, we work to build the next generation of systems that manage risk, create efficiency and improve transparency within the firm and across our broad community of investors and portfolio companies.

BXTI is nimble and entrepreneurial – our open, iterative design processes and rapid pace of development mean that everyone on the team has the opportunity to make an impact from day one. We are problem solvers who can take projects from idea to implementation. We believe in active mentoring and developing excellence. We collaborate to find the best answers for our customers and for Blackstone. We are critical to the firm maintaining its competitive edge.

The Role:

We are looking for a talented and enthusiastic Data Platform Engineer to join our team. In this role, you will work on building, maintaining, and optimizing the infrastructure and tools that enable data scientists and analysts to efficiently develop, deploy, and scale data science solutions. This position is ideal for someone with a strong interest in the intersection of data science, software engineering, and cloud infrastructure, and who is eager to learn in a fast-paced environment.

Key Responsibilities:

• Platform Development and Maintenance:

  • Assist in designing, building, and maintaining scalable and reliable data platforms and pipelines.

  • Support the integration of tools and frameworks for data ingestion, preprocessing, model training, and deployment.

• Infrastructure Management:

  • Work with cloud platforms (e.g., AWS, Azure, Google Cloud) to set up and manage computer resources, storage, and networking for data workflows.

  • Monitor and optimize platform performance, ensuring high availability and cost efficiency.

• Collaboration with Data Science and Analytic Teams:

  • Collaborate with data scientists and analysts to understand their requirements and provide solutions to streamline their workflows.

  • Assist in deploying machine learning models to production environments and setting up CI/CD pipelines.

• Automation and Tooling:

  • Develop scripts and tools to automate repetitive tasks and improve platform usability.

  • Implement version control and reproducibility best practices for data science projects.

• Security and Compliance:

  • Ensure that the platform adheres to security, privacy, and compliance standards.

  • Assist in managing access controls and permissions for data and platform resources.

• Continuous Learning and Improvement:

  • Stay up-to-date with the latest technologies and best practices in data science, data engineering, MLOps, and cloud computing.

  • Participate in team discussions to improve platform architecture and processes.

Required Qualifications:

• 4 + years of Data Platform Engineering experience in an enterprise environment.

• Proficiency in programming languages such as Python, Scala and SQL.

• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data-related services.

• Basic understanding of containerization and orchestration tools (e.g., Docker, Kubernetes).

• Knowledge of data pipelines and ETL proc