Data Engineer

PitchBook Data•Seattle, WA

4h•$129,000 - $155,000•Onsite

About The Position

As a member of the Product and Engineering team at PitchBook, 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! As a Data Engineer on the Enterprise Data Platform team, you will be responsible for building data pipelines to ingest various source data from enterprise technologies and PitchBook Platform data, manipulating (cleanse, dedupe, normalize) data into well-constructed data models for data analysis, implementing business logic and standard calculations, governing (supporting, observing, documenting) the data, and making the data available to end consumers in the form of PitchBook data products built on top of our data warehouse / data lake (e.g. Snowflake). You’ll work with a range of data and reporting technologies (e.g. Python, Docker, Tableau, Power BI) to build upon a strong foundation of rigor, quantitative techniques, and efficient processing. You’ll join other Engineers and Analytics professionals as part of the team that develops data pipelines and insights for our internal stakeholders across Sales, Customer Success, Marketing, Research, Data Operations, Product, Finance, and Administration. Your team will rely on you to build your skills in data techniques and analytics to deliver accurate, timely, accessible, and secure data & insights to users. You’ll collaborate closely and effectively with internal and external stakeholders of different roles and technical backgrounds, who have varying understanding of data engineering. You’ll have the opportunity and ability to impact many different areas of analytics and operational thinking across enterprise technology and product engineering. 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. If you love building data-centric solutions, strive for excellence every day, are adaptable and focused, and believe work should be fun, come join us!

Requirements

Bachelor's degree in a related field (Computer Science, Engineering, etc.)
2+ years of experience in data engineering roles, including creating and maintaining data pipelines, data modeling, and data architecture
3+ years of experience in advanced SQL, including expert-level skills in querying large datasets from multiple sources and developing automated reporting
2+ 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)
Proficiency in data storage solutions, data warehousing, and cloud-based data platforms (e.g. Snowflake)
Knowledge and applicable working experience establishing and ensuring data governance, data quality, and compliance standards
Exceptional problem-solving skills
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 Haves

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

Responsibilities

Apply 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
Build data models to be used for reports and dashboards used to translate business data into insights, identify and prioritize operational improvement opportunities, and measure business KPIs
Contribute to the ongoing improvement of quality assurance standards and procedures
Support the vision and values of the company through role modeling and encouraging desired behaviors
Participate in various company initiatives and projects as requested