Senior Software Engineer (R12079)

Company Overview:

At Oportun, we are on a mission to foster financial inclusion for all by providing affordable and responsible lending solutions to underserved communities. As a purpose-driven financial technology company, we believe in empowering our customers with access to responsible credit that can positively transform their lives. Our relentless commitment to innovation and data-driven practices has positioned us as a leader in the industry, and we are actively seeking exceptional individuals to join our team as Senior Software Engineer to play a critical role in driving positive change.

Position overview

We are seeking a highly skilled Platform Engineer with expertise in building self-serve platforms that combine real-time ML deployment and advanced data engineering capabilities. This role requires a blend of cloud-native platform engineering, data pipeline development, and deployment expertise. The ideal candidate will have a strong background in implementing data workflows, building platforms to enable self-serve for ML pipelines while enabling seamless deployments.

Responsibilities

Platform Engineering

• Design and build self-serve platforms that support real-time ML deployment and robust data engineering workflows.
• Create APIs and backend services using Python and FastAPI to manage and monitor ML workflows and data pipelines.

Real-Time ML Deployment

• Implement platforms for real-time ML inference using tools like AWS SageMaker and Databricks.
• Enable model versioning, monitoring, and lifecycle management with observability tools such as New Relic.

Data Engineering

• Build and optimise ETL/ELT pipelines for data preprocessing, transformation, and storage using PySpark and Pandas.
• Develop and manage feature stores to ensure consistent, high-quality data for ML model training and deployment.
• Design scalable, distributed data pipelines on platforms like AWS, integrating tools such as DynamoDB, PostgreSQL, MongoDB, and MariaDB.

CI/CD and Automation

• Use CI/CD pipelines using Jenkins, GitHub Actions, and other tools for automated deployments and testing.
• Automate data validation and monitoring processes to ensure high-quality and consistent data workflows.

Documentation and Collaboration

• Create and maintain detailed technical documentation, including high-level and low-level architecture designs.
• Collaborate with cross-functional teams to gather requirements and deliver solutions that align with business goals.
• Participate in Agile processes such as sprint planning, daily standups, and retrospectives using tools like Jira.

Required Qualifications

Experience

• 5-10 years experience in IT
• 5-8 years experience in platform backend engineering
• 1 year experience in DevOps & data engineering roles.
• Hands-on experience with real-time ML model deployment and data engineering workflows.

Technical Skills

• Strong expertise in Python and experience with Pandas, PySpark, and FastAPI.
• Proficiency in container orchestration tools such as Kubernetes (K8s) and Docker.
• Advanced knowledge of AWS services like SageMaker, Lambda, DynamoDB, EC2, and S3.
• Proven experience building and optimizing distributed data pipelines using Databricks and PySpark.
• Solid understanding of databases such as MongoDB, DynamoDB, MariaDB, and PostgreSQL.
• Proficiency with CI/CD tools like Jenkins, GitHub Actions, and related automation frameworks.
• Hands-on experience with observability tools like New Relic for monitoring and troubleshooting.