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.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal EntitySkills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 8+ years of experience in data engineering or related roles
- 2-3 years of leadership experience managing technical teams
- Experience designing and maintaining large-scale data architectures, pipelines, and data models in cloud environments
- Advanced proficiency in SQL and Python
- Deep understanding of ETL/ELT frameworks, data orchestration tools such as Airflow, and distributed messaging systems such as Kafka
- Strong knowledge of data governance, data quality, and compliance frameworks
- Experience with enterprise data sources such as CRM, ERP, marketing automation, and financial systems
- Hands-on experience with AI/ML platforms, model deployment, or data-driven automation
- Excellent communication and stakeholder management skills
- Demonstrated ability to build high-performing teams and lead through change
What the Team is Saying
Morningstar Compensation & Benefits Highlights
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Leave & Time Off Breadth — Time-off policies include flexible PTO and a paid sabbatical every four years, often highlighted as a standout perk. Feedback suggests this structure supports strong work–life balance and meaningful breaks.
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Parental & Family Support — Policies advertise a global minimum of 16 weeks for primary caregivers, up to 8 weeks for secondary caregivers, and at least six weeks of paid caregiving leave. These offerings signal above-average support for family and caregiving needs.
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Retirement Support — Retirement programs feature employer 401(k) contributions/matching, with some postings citing a 75% match on up to 7% of pay. Feedback suggests these offerings are a strong pillar of the package.
Morningstar Insights
What We Do
We are a global investment research and financial data company with 40-plus offices across North America, Europe, Australia, and Asia. Our products and services are used daily by individual investors, financial advisors, asset managers, retirement plan providers, and institutional investors. We provide data, research, and analysis across managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. The financial system can have real barriers—hidden information, friction that can slow decisions, and forces that can limit transparency and access. We work to remove them, bringing independent research, connected data, and investor-first tools to a system that needs more clarity. The people doing this work span research, technology, design, product, sales, and functional areas. We build many of our products in-house, so the work can connect directly to the tools investors use to make real financial decisions.
Why Work With Us
Morningstar’s missing is to empower investor success. We can only do that if our people feel empowered. That means finding people who think independently, bring a wide range of backgrounds with analytical rigor and genuine intellectual curiosity to the work.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.
