Senior Data Engineer

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 while ensuring data quality and system reliability. Work under minimal supervision and use a complete understanding of business needs and objectives to support projects that impact operational goals. Requires advanced skills and proficiency with relevant 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.

• Support 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 the relevant business area or specialization.

• Advanced knowledge of programming languages, including Python, Java, and SQL.

• Experience with data management and processing tools.

• Experience with data integration and processing tools.

• Experience with cloud services such as Databricks and Azure.

• Advanced problem-solving skills.

• Advanced communication and collaboration skills, with the ability to manage multiple priorities effectively.

• Advanced skills in data system design and a solid understanding of data warehousing, ETL processes, and big data technologies.

• Advanced knowledge of data engineering principles, technologies, and architecture.