About this role
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
In this role you will Build robust batch/streaming data pipelines and transformations that ensure high‑quality, governed data flows into AI and analytics platforms. Implement data modeling, quality checks, lineage/metadata, performance optimization, and reliable orchestration across cloud and Lakehouse environments. The position is located in New York, NY.
In this role, you’ll make an impact in the following ways:
- Design, build, and optimize batch and streaming data pipelines that deliver high-quality, governed data to AI, analytics, and enterprise platforms.
- Develop scalable transformation frameworks across cloud and Lakehouse environments with a strong focus on reliability, performance, and cost efficiency.
- Implement data modeling, schema design, lineage, metadata, and data quality controls to create trusted, reusable data assets.
- Build and support orchestration and workflow automation for complex pipelines and dependencies using modern data engineering tools.
- Partner with analytics, AI, business, and technology teams to translate requirements into scalable, secure, and governed data solutions.
- Resolve complex platform and pipeline issues related to performance, reliability, integration, and data quality.
- Promote engineering best practices in distributed processing, testing, monitoring, security, and continuous improvement.
- Provide technical leadership and mentoring while contributing to the adoption of modern data engineering and Lakehouse capabilities.
To be successful in this role, we’re seeking the following:
- Bachelor’s degree in computer science, Engineering, or a related field, or equivalent experience.
- 6+ years of experience in software development and data engineering; financial services experience is a plus.
- Strong experience building large-scale batch and streaming data pipelines and backend data environments.
- Deep expertise in Spark/Databricks, Kafka, SQL, and orchestration tools such as Airflow and/or dbt.
- Strong understanding of cloud and lakehouse architectures, distributed processing, and storage formats such as Parquet and Delta.
- Experience with data modeling, schema design, lineage, metadata, and data quality frameworks.
- Proven ability to improve performance, scalability, reliability, cost efficiency, and governance across data platforms.
- Strong stakeholder management, problem-solving, and technical leadership skills, including mentoring engineers and leading complex delivery.