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BNY

Safeguards and moves assets for investors

Senior Director Data Delivery Lead

Data EngineeringConfirmed live in the last 24 hours
Full-time$136.5k - $275k /yrIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
  • 15 or more 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.

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 software engineering discipline, including code quality, automated testing, CI/CD, observability, and documentation.
  • Drive engineering excellence across the delivery lifecycle, focusing on stability, maintainability, performance, and reuse.
  • Ensure data solutions are production-ready and aligned with 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 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 and judgment, converting 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 communication, partnership, and credibility.
  • Identify and address technical debt, platform gaps, and delivery risks proactively and systematically.
  • Contribute to longer-term platform strategy while ensuring 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 technical and non-technical stakeholders.
  • Mentor team members and help elevate engineering and delivery practices across the organization.

Desired Qualifications

  • 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.

About the Company

BNY

Safeguards and moves assets for investors

BNY safeguards financial assets and runs investment services for institutions, investment firms and wealthy clients around the world. Its custody business keeps clients' securities safe and handles the records and transactions needed to administer investment funds. Banks and brokers use its systems to settle trades, manage collateral and send payments, while its investment and wealth businesses manage portfolios and advise clients. It earns servicing and management fees as well as interest on loans and securities funded by client deposits. BNY traces its roots to the Bank of New York, founded by Alexander Hamilton in 1784, and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1784

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