Sr. Data Engineer, Analytics Engineering
Morningstar, Inc.Match Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level data engineer title, metro location, and popular skillset create high applicant competition.
Core data engineering skills (SQL, Python, ELT, Snowflake) are broadly transferable across industries.
Explicit 5+ years plus specific tech stack and tooling requirements raise shortlisting strictness to high.
Job Description
Structured overview of role & requirementsAbout This Role
Build and maintain data pipelines and models to support data analysis and business intelligence across enterprise technologies and PitchBook platform data.
Implement and govern data processes including cleansing, deduplication, normalization, and business logic for data products on Snowflake data warehouse.
Collaborate with internal stakeholders to deliver accurate, secure, and timely data and insights using technologies such as Python, Docker, Tableau, and Power BI.
Minimum Requirements
Bachelor's degree in Computer Science, Engineering, or related field.
Minimum 5 years experience in data engineering including pipeline creation, data modeling, and architecture.
Expertise in advanced SQL (5+ years) and Python scripting (3+ years) for data pipelines and analysis.
Experience with ETL/ELT processes, Airflow, Kafka, data warehousing (e.g. Snowflake), and data governance standards.
Ideal Candidate Profile
Experienced senior data engineer skilled in building and evolving scalable data pipelines and models using modern data and reporting technologies.
Ability to work cross-functionally with technical and non-technical stakeholders to translate business needs into data solutions.
Proficient in data governance, quality assurance, and managing complex enterprise data sources (CRM, ERP, financial systems).