Sr. Data Engineer

PitchBook PitchBook · Fintech · Seattle, WA · Enterprise Technology

This role is for a Sr. Data Engineer at PitchBook, a Morningstar company. The primary responsibilities include building unified data technologies, designing and maintaining database and reporting structures, defining and developing ELT processes and data modeling solutions, and establishing reports and dashboards to translate business data into insights. The role also involves mentoring junior engineers and staying updated on data engineering trends. The required skills include a Bachelor's degree, 5+ years of experience in data engineering, data pipelines, data modeling, data architecture, data cleansing, governance, quality, advanced SQL, Python, ETL/ELT processes, data alerting, data observability, data storage solutions, data warehousing, cloud platforms, and containerized deployment environments. Experience with enterprise technologies is a plus. The compensation is $140,000-$170,000 annually with a 10% target bonus.

What you'd actually do

  1. Expert at building unified data technologies to support advanced and automated business analytics
  2. Design, develop, document, and maintain database and reporting structures used to compile insights
  3. Define, develop, and review extract, load, and transform (ELT) processes and data modeling solutions
  4. Consistently evolve data processes and techniques following industry best practices
  5. Establish and help define reports and dashboards used to translate business data into insights, identify and prioritize operational improvement opportunities, and measure business KPIs against objectives

Skills

Required

  • Bachelor's degree in a related field (Computer Science, Engineering, etc.)
  • 5+ years of experience in data engineering roles, including creating and maintaining data pipelines, data modeling, and data architecture
  • 5+ years of experience in data cleansing, governance, and quality/integrity
  • 5+ years of experience in advanced SQL, including expert-level skills in querying large datasets from multiple sources and developing automated reporting
  • 5+ years of experience in Python, with skills for diverse components of data pipelines, including scripting, data manipulation, custom extract, transform and loads, and statistical/regression analysis
  • Expertise in extract, transform, and load (ETL) and extract, load, transform (ELT) processes and pipelines, platforms (e.g. Airflow), and distributed messaging (e.g. Kafka)
  • Experience with tools that capture and control data modeling change management (e.g. SQLMesh)
  • Experience building data alerting & notifications (e.g. on deviations, thresholds, etc.)
  • Experience building and managing tools for data observability and documentation (e.g. DataLab)
  • Proficient in data storage solutions, data warehousing, and cloud-based data platforms (e.g. Snowflake)
  • Proficient in deploying data pipelines to a cloud-native, containerized deployment/delivery environment (e.g. Kubernetes)
  • Knowledge and applicable working experience establishing and ensuring data governance, data quality, and compliance standards
  • Exceptional problem-solving skills and a track record of designing and optimizing data pipelines
  • Excellent communication and collaboration skills with the ability to engage with non-technical stakeholders
  • Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Nice to have

  • Experience working with enterprise technologies (CRM, ERP, Marketing Automation Platforms, Financial Systems, etc.) is a plus