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PitchBook

Private market data platform and analytics

Data Engineering Manager - Enterprise Data Platform

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSeattle, WA, USA$225k - $260k /yr

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science or Engineering is required.
  • At least 8 years of experience in data engineering is required.
  • At least 2 years of leadership experience managing technical teams is required.
  • Must be authorized to work in the United States without needing visa sponsorship now or in the future.
  • Proven experience designing and maintaining large-scale data architectures, pipelines, and data models in cloud environments such as 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 such as Airflow, and distributed messaging systems such as Kafka.
  • Strong knowledge of data governance, quality, and compliance frameworks.
  • Experience working with enterprise data sources such as CRM, ERP, marketing automation, or financial systems.
  • Hands-on experience with AI/ML platforms, model deployment, or data-driven automation.
  • Ability to communicate with stakeholders and translate complex data concepts into business value.
  • Demonstrated ability to build high-performing teams and lead through change.

Responsibilities

  • Lead, mentor, and retain data engineering talent and develop a team of data engineers, fostering excellence, accountability, and continuous improvement.
  • Define and drive the data engineering roadmap in alignment 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 innovation, operational rigor, and customer empathy within the data organization.
  • Oversee the design, development, and maintenance of data pipelines and ELT/ETL workflows across enterprise systems and the PitchBook platform.
  • Ensure scalable, secure, and reliable data architectures using modern cloud technologies such as Snowflake, Airflow, Kafka, and Docker.
  • Lead AI learning initiatives and integrate AI/ML-driven solutions into data products to improve 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.
  • Support the company's vision and values by role modeling and encouraging desired behaviors.
  • Participate in company initiatives and projects as requested.

Desired Qualifications

  • Experience working with enterprise data sources such as CRM, ERP, marketing automation, or financial systems is preferred.
  • Hands-on experience with AI/ML platforms, model deployment, or data-driven automation is a strong plus.

About the Company

PitchBook

Private market data platform and analytics

PitchBook provides private market data through the PitchBook Platform, a suite of software that gives users access to a comprehensive database of venture capital, private equity, and M&A activity. Users subscribe to tiered access to find information on companies, deals, investors, funds, and market players, and to perform due diligence and trend analysis. Revenue comes from subscription fees, plus advertising and partnerships around industry reports, news analysis, and blog content, serving investment professionals, executives, and advisors in Europe and North America. Its goal is to help clients stay ahead of industry trends and make informed investment and strategic decisions by providing accessible, structured private market data.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$13.8M
Headquarters
Seattle, WA
Founded
2007

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