Manager, Engineering, Enterprise Data Platform

Overview

Lead a team of data engineers within the Enterprise Data Platform team at PitchBook, owning data pipelines, large-scale data models, and the quality, availability and performance of enterprise data assets, while also shaping an analytics environment built for both people and AI agents.

What you'll do

• Lead, mentor, retain 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
• Build an analytics environment for AI agents as well as people, including semantic layers, governed metrics, rich metadata, agent-safe access and evaluation of agent output

What you'll need

• 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
• 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

Nice to have

• Experience working with enterprise data sources (CRM, ERP, Marketing Automation, Financial Systems, etc.)
• Hands-on experience with AI/ML platforms, model deployment or data-driven automation

Details

• Location: Mumbai, India
• Hybrid work model: four days in-office each week in most locations
• Standard office working conditions; limited corporate travel may be required to remote offices or business meetings and events