Lead Data Engineer

PitchBook Data•Seattle, WA

6d•$175,000 - $220,000•Onsite

About The Position

At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We’re deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company. Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there’s going to be some ambiguity along the way, but we excel when we challenge ourselves. We’re willing to take risks, fail fast, and do it all over again in the pursuit of excellence. If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you. At PitchBook, we believe that the Data Operations team plays a vital role in setting us apart from our competitors. We take immense pride in providing top-quality data to our customers, while also being accountable, collaborative, and receptive to feedback. Our team members are highly engaged, detail-oriented, and always eager to learn and grow as our industry evolves. Our reputation for excellence is a direct result of our deep commitment to building the world's best private market database, and we recognize the importance of investing in our team members from day one. That's why we offer specialized training and a mentorship program that is tailored specifically to the needs of the Data Operations team. We value and celebrate the diverse perspectives, talents, and experiences of our team members and recognize the importance of building trust and strong cross-functional partnerships. If you're looking for a challenging and rewarding opportunity to take your career to new heights, we invite you to join us at PitchBook.

Requirements

Bachelor’s degree in computer science, Engineering, Statistics, Information Systems, or related field
5+ years of experience in data engineering or related roles
Advanced SQL skills and strong experience working with large, complex datasets
Strong Python experience for data processing, automation, and pipeline development
Proven experience building and maintaining ETL/ELT pipelines (batch and event driven) and data workflows
Experience with data warehousing concepts and modern data stacks (e.g., Snowflake or similar)
Ability to design scalable, maintainable data models and systems
Strong communication skills, with the ability to work effectively with both technical and non-technical stakeholders
Demonstrated experience mentoring or guiding other engineers (formally or informally)
Experience working with large-scale proprietary data environments
Familiarity with orchestration tools (e.g., Airflow) and modern data tooling
Experience with BI tools such as Tableau or Power BI
Exposure to cloud platforms (AWS, Azure, or GCP)
Experience improving data quality, observability, and governance practices
Experience applying AI/ML or automation techniques to improve operational efficiency
Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Responsibilities

Lead the design and development of scalable data pipelines and workflows that support Data Operations
Define and implement best practices for data modeling, pipeline orchestration, testing, and monitoring
Drive improvements in data architecture, including warehousing, transformation layers, and data access patterns
Identify opportunities to modernize tooling, improve performance, and reduce operational overhead
Act as a technical mentor and coach a team of data engineers with diverse experience levels
Uplevel the team’s capabilities in SQL, Python, data modeling, and system design
Establish coding standards, review processes, and develop best practices
Help bridge the gap between operationally minded team members and software engineering rigor
Serve as the primary technical point of contact for Data Operations leadership and key stakeholders
Partner with Product, Engineering, and Data Platform teams to align architecture and shared capabilities
Translate business and operational needs into clear technical requirements and solutions
Influence prioritization and roadmap decisions within Data Operations initiatives
Build and maintain data solutions that integrate human-driven workflows with automated systems
Develop reporting and monitoring solutions to ensure data quality, pipeline reliability, and operational visibility
Deeply understand Data Operations processes and identify opportunities for automation and optimization
Balance speed and quality in a fast-moving, ambiguity-rich environment
Support the vision and values of the company through role modeling and encouraging desired behaviors
Participate in various company initiatives and projects as requested