Data Engineer, Associate - Cloud & Platform Engineering

Data Engineer

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 seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will have a strong background in data engineering best practices, cloud-based data platforms, and modern data pipeline development. This role will focus on designing, building, and maintaining scalable data solutions while ensuring cost optimization, security, and high-quality data delivery.

Responsibilities:

• Design, implement, and maintain Python-based data pipelines using tools like Prefect and Airflow.
• Manage Snowflake environments, including cost optimization, RBAC design, and performance tuning.
• Implement robust data quality frameworks to ensure accuracy, consistency, and reliability of data across systems.
• Leverage AWS services such as S3, Lambda, PrivateLink, and VPC to build secure and scalable data solutions.
• Develop and maintain DBT (Core/Cloud) models for data transformation and analytics workflows.
• Utilize Git-based SDLC practices to manage code repositories for ELT/ETL pipelines and other related services.
• Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Effectively communicate complex technical concepts to both technical and non-technical stakeholders.

Qualifications:

• 3+ years of experience in data engineering.
• Strong understanding of modern data engineering principles and methodologies.
• Proven experience in Snowflake administration, including query tuning, cost optimization, and RBAC, and disaster recovery.
• Advanced skills in Python for building and managing data pipelines.
• Experience with Git for version control and collaborative development workflows.
• Implement and monitor data quality frameworks.
• Hands-on experience with AWS services, particularly S3, Glue, Lambda, PrivateLink, and VPC.
• Familiarity with networking protocols such as TCP/IP, DNS, TLS, and SFTP
• Experience with DBT Core/Cloud for data transformation and modeling.
• Proficiency in tools like Prefect and Airflow for managing workflows.
• Clearly articulates technical concepts in written and spoken communication.
• Clarifies ambiguous requirements from non-technical stakeholders.
• Experience with lakehouse architectures, financial data, or private equity is a plus.
• Must be willing to participate in an on-call rotation.
• Experience using Jira to manage tasks, track progress, and collaborate in Agile or Scrum environments.