Senior Staff Data Engineer

We are seeking a highly skilled and experienced Senior Staff Data Engineer to join our dynamic team. The right candidate shall lead the development of our data infrastructure, from ingestion, ETL / ELT, aggregations, processing, quality checks, certifying data to regulatory standards, and making the data available for usage in analytics, data science, and CXO suite dashboards. Your work enables us to deliver advanced and impactful solutions to our clients. As the Senior Staff Data Engineer at Oportun, you will assume a pivotal role in elevating our data engineering capabilities, responsible for conceiving and implementing a state-of-the-art data infrastructure. Collaborating seamlessly with diverse teams, including data engineers, data scientists, engineers, analysts, product managers, and senior leaders, you will craft revolutionary solutions that redefine the norms of FinTech. Your profound expertise in architecting and deploying data architectures will be instrumental in propelling our products to new dimensions of sophistication and success.

 

Responsibilities

• Set the strategic vision and lead the implementation of a cutting-edge data infrastructure roadmap, encompassing all facets as highlighted above.
• Provide exceptional technical leadership, mentoring, and guidance to a team of data engineers, fostering a culture of continuous learning and innovation.
• Collaborate closely with data scientists to translate intricate model requirements into optimized data pipelines, ensuring impeccable data quality, processing, and integration.
• Spearhead the establishment of best practices for model versioning, experiment tracking, and model evaluation to ensure transparency and reproducibility.
• Engineer automated CI/CD pipelines that facilitate seamless deployment, monitoring, and continuous optimization for code and configurations in data engineering.
• Define and refine performance benchmarks, and optimize data infrastructure to achieve peak correctness, availability, cost efficiency, scalability, and robustness.
• Highly motivated self-starter who loves ownership and responsibility while working in a collaborative and interdependent team environment.
• Work with multiple teams of data engineers to design, develop, and test major software and data systems components using an agile, scrum methodology.
• Drive strong data engineering practices around product development execution, operational excellence in observability, quality, reliability, and developer efficiency.
• Remain at the forefront of industry trends and emerging technologies, expertly integrating the latest advancements into our data ecosystem.

Qualifications

• Requires 12+ years of related experience in data engineering, with a Bachelor's degree in Computer Science; or a Master's degree with an equivalent combination of education and experience.
• Extensive experience orchestrating the development of end-to-end data engineering infrastructure for intricate and large-scale applications.
• Proven record of transformative leadership, guiding technical teams to achieve remarkable outcomes and innovation.
• Profound mastery of data engineering architecture and frameworks across batch and stream processing of data, such as Hadoop ecosystem, Medallion architecture, Databricks or equivalent data warehouse / data lake platforms, coupled with Python / PySpark programming. 
• Thorough comprehension of software engineering principles, version control (Git), and collaborative development workflows.
• Adeptness with cloud platforms (AWS / Azure / GCP) and utilization of cloud-native services for crafting robust data engineering infrastructure.
• Track record of successfully integrating DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines.
• Superior problem-solving acumen and ability to navigate intricate technical challenges with dexterity.
• Exceptional communication aptitude, capable of fostering effective collaboration across diverse teams and stakeholders.

Preferred Skills

• Experience or Knowledge in financial services domain.
• Experience or Knowledge of one or more data processing frameworks using AWS will be a strong plus.
• Ability to handle multiple competing priorities in a fast-paced environment.