OneMain Financial Jobs

Company Description Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description The Principal Data Engineering Lead is a senior technical leader responsible for guiding the design, development, and optimization of Visa's largescale data platforms and cloud-based analytics environments. This role provides architectural direction, leads complex engineering initiatives, and mentors teams while remaining deeply hands-on with modern data technologies. The Lead Data Engineer drives technical best practices, ensures platform scalability, and influences data engineering strategy for key products and business domains. Responsibilities: Lead the architecture and delivery of large-scale, high-performance data pipelines and processing frameworks across Hadoop and multi-cloud environments. Design scalable data models, lakehouse structures, and distributed data processing solutions that support analytics, machine learning, and real-time data needs. Provide technical leadership to Senior and Staff Data Engineers, conducting design reviews, guiding implementation decisions, and ensuring engineering excellence. Partner with cross-functional teams to translate business and product requirements into robust technical designs and data solutions. Develop and improve engineering best practices for data governance, quality, observability, testing, and cloud resource optimization. Drive adoption of cloud-native data technologies, automation frameworks, and reusable components that improve development velocity and system reliability. Lead complex data modernization efforts, including cloud migration, data lake/lakehouse consolidation, and performance optimization of critical pipelines. Evaluate new tools and technologies, influencing platform evolution within the scope of assigned domains or product areas. Collaborate with product, analytics, and platform teams to ensure alignment on data strategy and architectural roadmaps. Mentor engineers at all levels, providing technical coaching and fostering a culture of continuous improvement. This is a hybrid position.Expectationofdays intheoffice will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 10+ years of relevant work experience with a Bachelor's Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience. Preferred Qualifications: 12 or moreyears of relevant work experience with a Bachelor's Degree or at least 7 or more years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13 or moreyears of relevant work experience.Advanced expertise in building and optimizing large-scale distributed data systems usingHadoop,Spark, and modern lakehouse architectures. Strong programming proficiency inPySpark, Scala, and Pythonwith experience implementing scalable, production-grade data applications. Deep experience designing and tuningRDBMS,NoSQL, and distributed SQL systems. Mastery ofSQLand distributed query engines such asPresto, Trino, Hive, and SparkSQL. Strong knowledge of data modeling, ETL/ELT design, and data warehousing methodologies. Proven experience architecting and operating data solutions onAWS, GCP, and Azure, including cloud data lakes, orchestration tools, and co