Senior Data Engineer (R13923)
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About the Role
ABOUT OPORTUN
Oportun (Nasdaq: OPRT) is a mission-driven financial services company that puts its members' financial goals within reach. With intelligent borrowing, savings, and budgeting capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $21.3 billion in responsible and affordable credit, saved its members more than $2.5 billion in interest and fees, and helped its members set aside an average of more than $1,800 annually.
WORKING AT OPORTUN
Working at Oportun means enjoying a differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture where we all feel a sense of belonging and are encouraged to share our perspectives. This inclusive culture is directly connected to our organization's performance and ability to fulfill our mission of delivering affordable credit to those left out of the financial mainstream. We celebrate and nurture our inclusive culture through our employee resource groups.
POSITION OVERVIEW
WHAT YOU'LL DO
- Lead the design and implementation of scalable, efficient, and robust data architectures to meet business needs and analytical requirements.
- Collaborate with stakeholders to understand data requirements, build subject matter expertise, and define optimal data models and structures.
- Design and develop data pipelines, ETL processes, and data integration solutions for ingesting, processing, and transforming large volumes of structured and unstructured data.
- Optimize data pipelines for performance, reliability, and scalability.
- Oversee the management and maintenance of databases, data warehouses, and data lakes to ensure high performance, data integrity, and security.
- Implement and manage ETL processes for efficient data loading and retrieval.
- Establish and enforce data quality standards, validation rules, and data governance practices to ensure data accuracy, consistency, and compliance with regulations.
- Drive initiatives to improve data quality and documentation of data assets.
- Provide technical leadership and mentorship to junior team members, assisting in their skill development and growth.
- Lead and participate in code reviews, ensuring best practices and high-quality code.
- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand their data needs and deliver solutions that meet those needs.
- Communicate effectively with non-technical stakeholders to translate technical concepts into actionable insights and business value.
- Implement monitoring systems and practices to track data pipeline performance, identify bottlenecks, and optimize for improved efficiency and scalability.
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