Quick overview
Job description
Job Title: Senior Data Engineer
Department: Non-Digital
Location: Hybrid@ Vienna, VA-attend F2F and Local to VA
Experience Level: 10+ years
Description
Design, develop, and optimize data pipelines and systems for the collection, connection, and storage of data. Manage,interpret, and derive insights from data. Implement data processing tasks, ensuring data quality and system reliability.Work under minimal supervision and use complete understanding of business needs and objectives to support projects that have impact on the achievement of operational goals. Advanced skill set and proficiency with procedures and techniques.
Responsibilities
· Design, develop and maintain data pipelines and workflows
· Collaborate with stakeholders to ensure data solutions align with business needs and goals
· Design and build robust data pipelines for data collection, connection, and storage
· Develop and maintain APIs and integrations to support secure, reliable data exchange across internal and external systems
· Support and enhance mortgage data platforms and data pipelines across the lending technology ecosystem
· Develop and enforce data engineering policies and best practices to ensure data integrity
· Ensure data quality and performance at scale
· Ensure high performance and scalability of data systems
· Help with the collection, connection, and storage of data
· Lead efforts to optimize existing data workflows and ensure system reliability
· Build working relationships with team members and subject matter experts
· Lead small projects and initiatives, taking a leadership role in planning and execution
· Mentor and guide junior data engineering team members
Qualifications
· Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field
· 5-7 years of experience in data engineering
· Complete knowledge and understanding of business area/specialization
· Advanced knowledge of programming languages (Python, Java, SQL)
· Experience with data management and processing tools
· Experience with data integration and processing tools
· Experience with cloud services (Databricks, Azure, etc.)
· Advanced problem-solving skills
· Advanced communication, collaboration skills and the ability to manage multiple priorities effectively
· Advanced skill in data system design and solid understanding of data warehousing, ETL processes, and big data technologies
· Advanced knowledge of data engineering principles, technologies, and architecture
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