Manager, Engineering, Enterprise Data Platform

As a Data Engineering Manager within the Enterprise Data Platform team at PitchBook, you will lead a team of skilled data engineers responsible for building and optimizing data pipelines, managing large-scale data models, and ensuring the quality, availability, and performance of enterprise data assets. This leadership role combines technical depth, strategic thinking, and people management to enable PitchBook’s data-driven decision-making and analytics capabilities.
You’ll collaborate closely with cross-functional partners across Technology & Engineering, Product, Sales, Marketing, Research, Finance, and Administration to deliver robust, scalable data solutions. The ideal candidate is a hands-on leader with a strong background in modern data platforms, cloud architecture, and team development—someone passionate about empowering teams and improving data capabilities across the organization. A core part of this role is shaping an analytics environment that is built for AI agents as much as for people. Our analysts, executives and AI agents should all query the same governed, documented, well-described data and get the same answers. You will lead the team to make that real, with semantic layers, governed metrics, rich metadata, agent-safe access, and evaluation of agent output, and in using agents to build faster and with higher quality.
This is both a strategic and hands-on leadership role: you will guide architectural decisions, mentor engineers, collaborate with cross-functional leaders, and contribute to building next-generation data and AI capabilities at PitchBook. You will exhibit a growth mindset, be willing to solicit feedback, engage others with empathy, and help create a culture of belonging, teamwork, and purpose. If you love leading a team of passionate data engineers, building data-centric solutions, strive for excellence every day, are adaptable and focused, and believe work should be fun, come join us!
Primary Job Responsibilities
Lead, mentor, retain top talent and develop a team of data engineers, fostering a culture of excellence, accountability, and continuous improvement
Define and drive the data engineering roadmap aligned with enterprise data strategy and business objectives
Collaborate with senior technology and business leaders to define data platform priorities, architecture, and long-term vision
Promote a culture of innovation, operational rigor, and customer empathy within the data organization
Oversee the design, development, and maintenance of high-quality data pipelines and ELT/ETL workflows across enterprise systems and PitchBook’s platform
Ensure scalable, secure, and reliable data architectures using modern cloud technologies (e.g., Snowflake, Airflow, Kafka, Docker)
Lead AI learning initiatives and integrate AI/ML-driven solutions into data products to enhance automation, predictive insights, and decision intelligence
Champion data quality, governance, lineage, and compliance standards across the enterprise data ecosystem
Partner with engineering and infrastructure teams to optimize data storage, compute performance, and cost efficiency
Support career development through mentoring, skill-building, and performance feedback
Skills And Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
8+ years of experience in data engineering or related roles, including at least 2–3 years of leadership experience managing technical teams
Proven experience designing and maintaining large-scale data architectures, pipelines, and data models in cloud environments (e.g., Snowflake, AWS, Azure, or GCP)
Advanced proficiency in SQL and Python for data manipulation, transformation, and automation
Deep understanding of ETL/ELT frameworks, data orchestration tools (e.g., Airflow), and distributed messaging systems (e.g., Kafka)
Strong knowledge of data governance, quality, and compliance frameworks
Experience working with enterprise data sources (CRM, ERP, Marketing Automation, Financial Systems, etc.) is preferred
Hands-on experience with AI/ML platforms, model deployment, or data-driven automation is a strong plus
Excellent communication and stakeholder management skills with the ability to translate complex data concepts into business value
Demonstrated ability to build high-performing teams and lead through change
Working Conditions
The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.
Morningstar India is an equal opportunity employer
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
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