Data Engineer

As a Data Engineer, you will work across a global team of analysts and data operation associates to develop new data technologies for Data Operations at PitchBook. We’re looking for a person who can combine proficiency in data engineering technologies (SQL, Python, Data Warehousing & ETL tools, Power BI) with an operational mindset and deliver powerful new data sourcing, automation and efficiency tools to the team. You will become a master PitchBook’s data operations processes and methodologies, establishing the process knowledge necessary to develop effective data solutions.

What you'll do:

• Extracting data from various sources, including web scraping, API requests, etc.
• Building complex data pipelines that automate data sourcing and processing.
• Develop programs to synchronize technology and human-powered processes.
• Design and maintain database and data warehousing solutions.
• Develop automated reports to monitor and track data pipelines (Power BI, Tableau)
• Work alongside Data Operations teams to augment core technologies.
• Play a key role in continuing to build out a newly formed data engineering function in the department.
• Serve as a data and engineering SME on cross-functional Data Operations initiatives.
• Mentor and assist Associate Data Engineers in building out pipeline architecture.

Preferred Qualifications

• Bachelor's degree in Engineering, Statistics, Computer Science, Economics, Business, Finance, or related fields.
• 2+ years of relevant experience working as a Data Engineer, Business Intelligence Engineer, and/or Data Analyst
• Advanced SQL skills, with experience querying large datasets from multiple sources and developing automated reporting. Experience with Snowflake is a plus.
• Advanced Python skills with experience in web scraping, OCR, REST APIs, data manipulation, and ETLs.
• Experience with software development best practices (e.g., unit testing, code reviews, design, continuous delivery, git, test automation and build\deploy systems).
• Familiarity with AWS cloud computing services.
• Familiarity with Docker, container orchestration, and workflow systems (ECS, Kubernetes, Airflow, etc.).
• Knowledge of statistical methods and regression analysis.
• Proficiency in Tableau or Power BI (both is a plus).
• Excellent Microsoft Office/PC skills, Advanced Excel experience analyzing data and creating daily/weekly/monthly reports.
• Ability to display complex quantitative data in a simple, intuitive format and to present findings in a clear and concise manner.
• Capable of investigating, familiarizing, and mastering new data sets quickly.
• Demonstrated project and stakeholder management skills.
• Excellent interpersonal skills, with the ability to communicate complex data issues correctly and clearly to both internal and external customers.

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. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

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