Job DescriptionThe Impact You Will Have in This RoleAs
Director, Data Engineering & Data Products, you will lead the strategy, engineering, and delivery of DTCC's next-generation data platforms and products. You will drive the creation of trusted, scalable, and business-critical data solutions that power decision-making, regulatory compliance, operational excellence, and client services across the enterprise.
This is a highly visible leadership role where you will partner with senior stakeholders across Product, Technology, Operations, Risk, Compliance, and Architecture to define the vision, roadmap, and operating model for enterprise data products. You will play a key role in advancing DTCC's data transformation strategy while building modern cloud-native capabilities on Snowflake and AWS.
If you are passionate about building high-performing teams, modernizing data platforms, and turning complex data challenges into strategic business outcomes, this is an opportunity to make a lasting enterprise-wide impact.
Your Primary Responsibilities:
- Define and execute the strategy, roadmap, and operating model for enterprise data products aligned with business and technology priorities.
- Lead the design, engineering, and delivery of scalable, secure, and trusted data solutions leveraging Snowflake and AWS.
- Partner with business and technology leaders to prioritize initiatives, drive adoption, and deliver measurable business value.
- Establish and promote modern engineering practices across DataOps, automation, observability, governance, quality, and platform reliability.
- Drive end-to-end delivery, including data ingestion, integration, transformation, orchestration, testing, deployment, and production support.
- Implement strong controls around data quality, metadata, lineage, security, privacy, and regulatory compliance.
- Evaluate and adopt emerging technologies, AI-enabled automation, and modern data platform capabilities to accelerate innovation and operational efficiency.
- Build, mentor, and lead high-performing engineering teams while managing priorities, risks, dependencies, budgets, and stakeholder expectations.
Qualifications - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
- 12+ years of progressive experience in Data Engineering, Data Architecture, Data Platforms, or related disciplines.
- Proven experience leading enterprise-scale data initiatives and managing high-performing technical teams.
- Experience operating successfully within complex, highly regulated environments preferred.
Talent Needed for Success - Deep expertise with Snowflake, AWS, and modern cloud-native data architectures.
- Strong experience building and scaling enterprise data products, platforms, and engineering organizations.
- Demonstrated success partnering with executive stakeholders to deliver strategic business outcomes.
- Expertise in data engineering concepts including ETL/ELT, CDC, API integrations, streaming, and event-driven architectures.
- Strong knowledge of Snowflake capabilities, including data sharing, governance, performance tuning, scalability, and cost optimization.
- Hands-on understanding of AWS services, cloud security, IAM, monitoring, resiliency, and automation.
- Experience implementing DataOps, CI/CD, automated testing, observability, and production support best practices.
- Strong expertise in data quality, metadata management, lineage, governance, privacy, and regulatory controls.
- Experience leveraging AI and automation technologies to improve engineering productivity, platform operations, and delivery efficiency.
Preferred Qualifications - Experience building data products within Financial Services, Capital Markets, FinTech, or Banking organizations.
- Knowledge of modern lakehouse technologies, including Apache Iceberg, Delta Lake, and Apache Hudi.
- Experience with Master Data Management (MDM) and enterprise data governance programs.
- Experience leading cloud modernization, technology transformation, and platform evaluation initiatives.
- Strong understanding of financial services data domains, including Risk, Regulatory Reporting, Trade & Position, Payments, KYC, and Reference Data.
The salary range is indicative for roles at the same level within DTCC across all US locations. Actual salary is determined based on the role, location, individual experience, skills, and other considerations.
