Senior Director, Data Delivery Lead

BNY Mellon•New York, NY
•$136,500

About The Position

BNY is seeking a highly effective Data Delivery Engineer to architect, build, and scale modern data products and platform capabilities across a complex, multi-business environment. This role requires a strong blend of hands-on engineering execution, platform architecture, strategic roadmap leadership, and organizational influence. The successful candidate will bring deep experience delivering enterprise-grade data solutions using modern technologies while also helping shape the target-state architecture for a scalable, resilient, and reusable data platform. This individual must be equally comfortable building software, driving technical direction, partnering across functions, and influencing platform decisions that extend beyond their immediate team.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
  • 15 plus years of experience in data engineering, software engineering, or data platform engineering.
  • Proven ability to deliver enterprise-scale data and software solutions in complex environments.
  • Strong hands-on experience with modern data technologies
  • Strong proficiency in Python, SQL, and at least one additional language such as Java or Scala.
  • Experience with distributed data processing and pipeline design using modern frameworks and tooling.
  • Experience with DevOps and software delivery practices including CI/CD, version control, automated testing, and infrastructure automation.
  • Strong understanding of data architecture, data modeling, large-scale systems design, and platform engineering concepts.
  • Demonstrated ability to influence technical decisions across teams and functions.
  • Strong communication and stakeholder management skills.

Nice To Haves

  • Experience building shared or multi-tenant enterprise data platforms.
  • Familiarity with open data ecosystem technologies such as Parquet, Delta Lake, or similar table and storage formats.
  • Experience with orchestration and workflow technologies such as Airflow or equivalent tools.
  • Experience with streaming and event-driven technologies such as Kafka or similar platforms.
  • Familiarity with containerization and cloud-native deployment approaches such as Kubernetes.
  • Experience with metadata, lineage, data quality, and governance tooling.
  • Experience operating in highly regulated, large-scale enterprise environments.
  • Exposure to modern data operating models, including data products, domain-oriented ownership, or data mesh-aligned patterns.

Responsibilities

  • Design, build, test, deploy, and support high-quality data products and platform capabilities for enterprise use cases.
  • Deliver scalable and reliable software solutions across batch, near-real-time, and event-driven data patterns, as needed.
  • Apply strong software engineering discipline, including code quality, automated testing, CI/CD, observability, and documentation.
  • Drive engineering excellence across the delivery lifecycle, with a focus on stability, maintainability, performance, and reuse.
  • Ensure data solutions are production-ready and aligned to enterprise standards for security, resiliency, and operational support.
  • Build modern data products that are consumable, well-governed, and aligned to business and platform objectives.
  • Contribute to the design and evolution of a large-scale, multi-business data platform supporting diverse data domains and consumption models.
  • Define and implement scalable patterns for ingestion, transformation, storage, metadata, lineage, access management, and delivery.
  • Develop reusable services, frameworks, and engineering patterns that accelerate delivery across teams.
  • Support cloud and hybrid data architectures using modern storage and compute approaches.
  • Architect enterprise-scale data capabilities leveraging Snowflake, Apache Iceberg, Oracle Exadata, Azure, and other relevant technologies.
  • Evaluate current-state architecture, identify opportunities for simplification and modernization, and recommend target-state solutions.
  • Make sound design decisions that balance business outcomes, risk management, scalability, cost, and speed of execution.
  • Contribute to enterprise engineering standards, architecture patterns, and platform guardrails.
  • Lead through technical depth, strong judgment, and the ability to convert strategy into practical engineering outcomes.
  • Translate business priorities and platform strategy into actionable technical roadmaps and delivery plans.
  • Partner with product, architecture, infrastructure, security, governance, and business stakeholders to align on priorities and sequencing.
  • Influence decisions across the broader organization through strong communication, partnership, and credibility.
  • Identify and address technical debt, platform gaps, and delivery risks in a proactive and structured way.
  • Contribute to longer-term platform strategy while ensuring strong near-term execution against commitments.
  • Work effectively across a matrixed organization and multiple lines of business.
  • Build strong relationships with engineering teams, platform teams, architects, and business partners.
  • Communicate complex technical topics clearly to both technical and non-technical stakeholders.
  • Mentor team members and help elevate engineering and delivery practices across the organization.
  • Demonstrate ownership, accountability, curiosity, and a strong bias for execution.
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