Morningstar
Website:
morningstar.com
Company:
https://www.linkedin.com/company/morningstar
Seniority: Director
Industries: IT System Data Services
Job details:
Senior Director – Data collection tech.
Team: The Data Collections Technology team is the foundational platform collection engine for PitchBook. Our mission is to architect, build, and operate the unified Acquisition, Processing, and Management Platforms that power PitchBook's proprietary data engine. We focus exclusively on engineering highly scalable, resilient, and secure systems that transform vast volumes of raw external data into structured, high-quality, and actionable data assets for the entire business.
As a core team of globally distributed Software Engineers, we are responsible for the architectural integrity and operational excellence of mission-critical systems, including the core ETL/ELT infrastructure, data storage services, and the frameworks that ensure robust data quality and governance.
We operate as a center of excellence for platform delivery, driving high-leverage outcomes by collaborating cross-functionally, cross-divisionally, and across business units. The Senior Director of this team, reporting to the Leader of Engineering, Data Collections Technology, will partner closely with Data Operations to industrialize data collection workflows, Data Collections Product to define platform capabilities, and peer Engineering teams to standardize best practices for large-scale data ingestion and processing. Our success is measured by the reliability, efficiency, and throughput of our data processing infrastructure, directly enabling the business to accelerate coverage and deliver timely insights to our customers.
As the Senior Director of Data Collections Technology, you will define and execute the comprehensive technology strategy for acquiring, processing, and integrating PitchBook’s proprietary public and private market data. You will be directly accountable for the teams building, and operating the end-to-end Data Collection pipelines and tools which empower PitchBook business. Solutions encompass robust, scalable ingestion pipelines, resilient data storage solutions, and the intelligent systems that ensure PitchBook’s data is as accurate, comprehensive, and timely as possible.
In this high-impact role, you will lead a diverse, global organization of Engineers driving both architectural innovation and operational excellence for mission-critical systems. You will define the multi-year technical roadmap for automation, scalability, and quality across all core data domains, ensuring the entire technology stack delivers production-grade reliability and directly powers PitchBook’s data ingestion and platform accuracy.
Your leadership will guide the design, deployment, and optimization of the entire technology ecosystem, from low-latency data acquisition services to coordinating with centralized AI/ML teams to leverage advanced AI-driven extraction and enrichment models (e.g., document AI, entity resolution, and quality validation). You will also play a key role in shaping the data colletions strategy across all of PitchBook and our parent company Morningstar, in collaboration with Product, Data Operations, and the core Engineering teams, ensuring consistency, reliability, and alignment with overarching business outcomes.
This role demands a technically credible and outcome-oriented leader with an AI first mindset. One who can balance strategic accountability with hands-on technical oversight, and who can influence executive stakeholders across the organization while ensuring the continued growth and professional development of a globally distributed, high-performing technical team.
Primary Job Responsibilities:
- Define and execute the unified platform technology strategy for data acquisition, processing, and management across the organization with an AI first mindset.
- Partner with senior leadership to define the multi-year engineering roadmap that drives scalability, reliability, and cost-efficiency in data collection.
- Establish and own operational KPIs for platform throughput, latency, and system availability across all production environments.
- Lead, hire, and develop a high-performing team of platform and software engineers; define clear roles and technical career progression.
- Foster a culture of engineering excellence, ownership, and accountability for critical production systems across distributed offices.
- Champion hiring, technical mentorship, and professional development initiatives to grow internal platform engineering talent.
- Elevate engineering excellence through technical guidance, design reviews, and architectural decision records (ADRs) for core platform engineers.
- Act as a multiplier by shaping and enforcing best practices for distributed systems design, CI/CD, and data pipeline governance.
- Guide and influence cross-functional, cross-division, and cross-business unit teams toward cohesive, reusable, and standards-aligned platform architectures.
- Collaborate closely with Engineering, Product, and Data Operations to ensure seamless delivery and integration of core platform services into collection workflows.
- Partner with data quality and governance teams to define and embed platform-level data quality frameworks and compliance standards.
- Serve as the trusted technical and strategic advisor on data collection platform capabilities to stakeholders across the business.
- Oversee the end-to-end lifecycle of the unified data collection platform, from architectural planning to deployment, monitoring, and optimization.
- Ensure high availability, nine-nines reliability, and performance of all mission-critical production platform services.
- Implement and maintain strong standards of data integrity, security, and governance across all platform components and data pipelines.
Skills and Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical discipline (Master’s degree preferred).
- 18+ years of experience in large-scale software engineering or platform architecture, including 7+ years leading technical teams; experience managing managers and geographically distributed teams is strongly preferred.
- Proven success designing and delivering high-throughput, low-latency data ingestion and processing platforms at scale within a commercial environment
- Deep, practical expertise in distributed systems architecture (e.g., event-driven architecture, microservices, stream processing), data modeling, and designing for system reliability and fault tolerance.
- Expert-level knowledge of cloud-native architecture (e.g., AWS, GCP, Azure), containerization (Docker, Kubernetes), and modern infrastructure-as-code (IaC) principles.
- Proficiency in managing and optimizing large-scale ETL/ELT pipelines and ensuring data governance and integrity within a complex, regulated data environment.
- Strong understanding of DataOps and MLOps principles as they apply to platform tooling, including automated deployment, monitoring, and performance optimization for critical data infrastructure.
- Demonstrated ability to define, communicate, and execute multi-year platform engineering roadmaps with measurable business impact on reliability and efficiency.
- Excellent communication, collaboration, and influencing skills—including experience presenting technical strategy to executive and cross-functional leadership.
- A track record of fostering technical excellence, quality assurance, and a security-first mindset across global, multidisciplinary teams.
- Experience in fintech, core data platforms, or large-scale information extraction systems is strongly preferred.
- Contributions to the platform engineering community (e.g., technical publications, open-source projects, or conference presentations on distributed systems) are a strong plus.
Morningstar is an equal opportunity employer.
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