Senior Data Engineer

About the job

As a Senior 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). Primary Job 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 against objectives • 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 Skills and Qualifications • 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 advanced SQL, including expert-level skills in querying large datasets from multiple sources and developing automated reporting • 3+ 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) • Exceptional problem-solving skills • Excellent communication and collaboration skills with the ability to engage with non-technical stakeholders

Requirements

• Data Engineering
• Python
• ETL Processes
• SQL
• Data Modeling

Qualifications

• Bachelor's degree in related field
• 5+ years of experience in data engineering
• 3+ years of experience in Python

Preferred Technologies

• Data Engineering
• Python
• ETL Processes
• SQL
• Data Modeling

About the company

Morningstar is an equal opportunity employer. Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis.