Job
Description
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 PitchBooks 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 developmentsomeone 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. **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 PitchBooks 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:** - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - 8+ years of experience in data engineering or related roles, including at least 23 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. 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.,
