Senior Staff Data Engineer

Job Description Job Description: - 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