Data Engineer, Aladdin Data, Associate

We are seeking a Data Engineer to join our Alternative Data Pipeline Engineering team, which supports Aladdin, BlackRock's investment management and technology platform.

As a Data Engineer, you will build and support enterprise data pipelines and data platforms that enable scalable processing of structured and semi-structured data.

Your responsibilities:

• 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.

Requirements:

• 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.

Benefits:

• A strong retirement plan
• Tuition reimbursement
• Comprehensive healthcare
• Support for working parents
• Flexible Time Off (FTO)