Engineering Manager, Enterprise Data Platform

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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