Principal Data Engineer PayPal

About PayPal

Job Description

The Company Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. Job Description: Your way to impact Your day to day In your day to day role you will Work independently or as a team member. Proactively remove obstacles to ensure timely delivery of product and goals Write clean and solid code that scales over PB of data and enforce engineering excellence in the organization Improve data management efficiency through AI capabilities, better process and best practices Embed Privacy-by-Design principles into all data solutions and ensure compliance with regulatory requirements. Provide expertise across the data product development lifecyclespanning data engineering, architecture, and analyticsto design and deliver reusable, accessible, and high-quality data solutions. Design data structures and taxonomies that support standardization, integration, and alignment with business processes. Deliver technical leadership through analytical thinking, innovation, and detailed specifications. Drive data product execution and adoption through a metrics-based approach Strong product sense to identify data challenges and opportunities, and assess the impact of data-driven solutions Leverage enterprise frameworks, governance tools, and reusable architecture patterns for Credit Risk and cross organizations Foster influential cross-functional relationships through collaboration, proactive planning, and decisive leadership to design scalable solutions across platforms and products. Technical Leadership Qualities: Strong collaboration skills and ability to influence across all organizations and levels within the company Ability to communicate clearly and succinctly to all levels within the organization- translating the organizations goals into execution plans & metrics Possess the ability to connect, engage and lead with empathy Motivate others through a shared vision and confidence that empowers employees and teams to perform at their best Demonstrate ability to delegate work Operate with transparency and honesty in all interactions What do you need to bring- 12+ years of experience in enterprise data management, with deep expertise in data governance, architecture, modelling, and platform design Proven experience enabling data products at scale within large, cross-functional organizations Strong technical acumen with the ability to quickly grasp the technical details of products and systems Expertise in data modelling using domain-driven design principles and a strong grasp of data architecture best practices. Proficient in building and optimizing data platforms and pipelines using streaming and batch processing, including Lambda and Kappa architectures Technical proficiency data management stacks and techniques such as Python, SQL, BigQuery, Airflow, Spark, Kafka, and data modelling, with experience in integrating ML/AI into scalable data solutions. Experience with cloud-based data platforms, preferably GCP, and associated services Demonstrated success in supporting ML/AI workloads (e.g., feature stores, training pipelines, model monitoring) and integrating AI into data workflows Familiarity with AI-enhanced data systems (e.g., automated data discovery, quality monitoring, ML-assisted ETL) Able to independently drive complex and ambiguous problem-solving efforts, balancing technical and strategic trade-offs Excellent verbal and written communication skills with the ability to collaborate effectively across engineering, risk, product, and compliance teams. Adaptive, self-motivated, and comfortable navigating shifting priorities while maintaining focus on the end-to-end impact of data across systems. Bonus Qualifications Proven experience bridging the gap between data engineering and machine learning engineering. Experience in financial services, with a strong preference for exposure to the credit risk domain. Education: BS or advanced degree in Engineering, Computer Science, or related technical field. Our Benefits: Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please dont hesitate to apply.,