Data Engineer

This role supports the Digital Collections team by managing data preparation and maintenance to ensure accuracy and accessibility for operational needs. The position involves delivering timely MIS and analytical reports to aid the collections team in effective decision-making. The candidate will serve as the primary contact for ad-hoc data requests related to collections, facilitating efficient data retrieval and usage. Additionally, the role focuses on identifying and implementing process improvements, including automation of manual workflows and optimization of data pipelines, to enhance scalability and efficiency.

The successful candidate will build and maintain the infrastructure necessary for seamless data extraction, transformation, and loading from multiple sources, utilizing SQL and AWS big data technologies. Collaboration with executive leadership, product, data, and design teams is essential to address technical challenges and improve data-driven strategies for collections and portfolio analysis. Ensuring the security of sensitive collections data in compliance with privacy regulations and company policies is a critical responsibility. The role also involves partnering with data and analytics experts to enhance system functionality for portfolio segmentation, delinquency management, and digital collection strategies. Leveraging digital collections technologies to analyze delinquent accounts and design proactive engagement strategies will improve collections workflow efficiency. Close collaboration with Digital Collections squads will support the development and regional expansion of the digital collections stack.

Key Responsibilities

- Assist Digital Collections with data preparation and maintenance, ensuring data accuracy and operational accessibility.
- Deliver Collections MIS and analytical reports promptly to support decision-making.
- Act as the primary point of contact for all ad-hoc collections data requests.
- Identify, design, and implement process improvements, including automation and optimization of data pipelines.
- Build and maintain data infrastructure using SQL and AWS big data technologies for ETL processes.
- Collaborate with leadership and cross-functional teams to resolve technical challenges and enhance data-driven collection strategies.
- Implement best practices for securing sensitive collections data, ensuring compliance with privacy regulations.
- Partner with data and analytics teams to improve data systems for portfolio segmentation and delinquency management.
- Utilize digital collections technologies to analyze delinquent accounts and develop proactive engagement strategies.
- Work with Digital Collections squads to enhance and expand the digital collections technology stack across regions.

Required Qualifications

- 3-5 years of experience in Retail Collections, Collections Strategy, Credit Operations, or Product Management.
- 2-3 years of hands-on experience with data management and MIS reporting.
- Strong understanding of collections processes and procedures.
- Ability to interpret data and extract meaningful trends.
- Knowledge of data architecture, data retention policies, performance monitoring, and infrastructure recommendations.
- Proficiency in Java, Scala, SQL, and SAS development.
- Expertise in big data systems including Hadoop ecosystem and cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with in-memory databases (e.g., HANA, Hazelcast) and traditional RDBMS (SQL Server, Oracle) as well as NoSQL databases.
- Comfortable with dashboard development tools such as Tableau, Power BI, or Qlik.
- Skilled in developing data analytics models using R, Python, or Spark.
- Bachelor’s degree in Computer Science or equivalent; Master’s degree preferred.
- Practical knowledge of data extraction and transformation tools.

This position offers the opportunity to work at the intersection of data engineering and collections strategy, driving innovation in digital collections technology and analytics to improve operational efficiency and portfolio performance.