Vice President, AI / Machine Learning Software Engineer

BNY Mellon•New York, NY

About The Position

The Vice President, AI / Machine Learning Software Engineer will build robust batch and streaming data pipelines and transformations that deliver high-quality, governed data to AI, analytics, and enterprise platforms. The position focuses on scalable data solutions across cloud and Lakehouse environments, with attention to reliability, performance, cost efficiency, and governance. The role is located in New York, NY. The engineer will develop data models and quality controls, establish schema design, lineage, and metadata practices, and build orchestration and workflow automation for complex pipelines. Working with analytics, AI, business, and technology teams, the role translates requirements into secure, scalable data solutions; resolves complex platform and pipeline issues; promotes engineering best practices; and provides technical leadership and mentoring while supporting modern data engineering and Lakehouse capabilities.

Requirements

Bachelor’s degree in computer science, engineering, or a related field, or equivalent experience.
At least 6 years of experience in software development and data engineering.
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.

Nice To Haves

Financial services experience.

Responsibilities

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, focusing 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 mentor engineers while contributing to the adoption of modern data engineering and Lakehouse capabilities.