Engineering Manager, Enterprise Data Platform

About the role

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. 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!

What you’ll do

• 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

What you’ll bring

• 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

Skills

Education

Bachelor's or Master's