Senior Vice President, AI / Machine Learning Data Engineer

About the role

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.

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 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.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 9–11 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.

Qualifications

• None specified

Skills

• 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.

Benefits

• Competitive compensation package including base salary, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.
• Flexible global resources and tools for your life’s journey.
• Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.

Pay

The base salary for this position is expected to be between $126,000 and $210,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.

Schedule

At-will position with the Company reserving the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.