About this role
Job title: Senior Data Engineer
About the Role As a Senior Data Engineer at Marathon Petroleum Corporation, you will design, develop, and optimize scalable data pipelines and cloud-based data solutions using modern data architecture and Azure data services, including Data Lake, Synapse Analytics, Azure Functions, and Databricks. You will partner with analytics, product, architecture, governance, and business teams to translate requirements into scalable data solutions. The ideal candidate has deep technical depth in Python, SQL, Spark, and orchestration tools such as Azure Data Factory or Databricks Workflows, a continuous improvement mindset, and the ability to mentor while contributing to engineering standards and reusable patterns.
What You'll Do
- Conducts the design, innovation and optimization of data extraction, ingestion and transformation processes.
- Facilitates the development and design of complex data architecture to process and store high-volume data sets.
- Enables the development of complex data pipelines; advocates for and implements data security and privacy measures.
- Conducts complex data quality and processing tasks using open source and cloud services.
- Provide technical expertise during critical incidents.
- Facilitates the adoption of best practices for data security and privacy and collaborates with other departments to ensure seamless data integration.
- Facilitates the implementation of continuous improvements in data processing methods and drives consistency and best practices across data engineering projects.
- Solves complex problems; takes a new perspective on existing solutions; participates in strategic planning sessions for data infrastructure.
- Oversee quality assurance and testing for data solutions.
- Mentors less experienced data engineers.
What We're Looking For
- Bachelor’s Degree in Information Technology, related field or equivalent experience
- 5+ years of relevant data engineering experience
- Proficiency in Python, SQL, Spark
- Experience with orchestration tools such as Azure Data Factory and/or Databricks Workflows
- Familiarity with big data technologies (Hadoop, Spark, distributed computing)
- Cloud Platform knowledge (Azure, AWS, or GCP)
- Data Governance, Data Integration, Data Lifecycle, Data Modeling, Data Operations, Data Pipelines, Data Privacy, Data Quality Management, Data Security
- Data Warehousing concepts and monitoring/observability practices
Nice to Have
- Experience mentoring less experienced data engineers
- Experience with Azure Databricks and Azure Data Factory
- Knowledge of data privacy regulations and secure data handling practices