Sr. Data Engineer

At Pitch Book, 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, Pitch Book is the place for you.

As a member of the Product and Engineering team at Pitch Book, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve.

Join our team and grow with us!

• Expert at building unified data technologies to support advanced and automated business analytics
• Design, develop, document, and maintain database and reporting structures used to compile insights
• Define, develop, and review extract, load, and transform (ELT) processes and data modeling solutions
• Consistently evolve data processes and techniques following industry best practices
• 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
• Contribute to the ongoing improvement of quality assurance standards and procedures
• Mentor and guide less experienced data engineers, contributing to their professional development
• Stay updated with the latest data engineering technologies and trends and share your insights with the team
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested

• 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. Data Lab)
• 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…