Staff Data Engineer at PayPal

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

11 Apr, 26

Salary

0.0

Posted On

11 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Architecture, Data Governance, Data Management, Collaboration, Mentorship, AI Capabilities, Data Quality, Technical Leadership, Data Analysis, Machine Learning, Credit Risk, Problem Solving, Communication, Execution Skills, Empathy

Industry

Software Development

Description

Lead and manage data engineering projects, ensuring timely delivery and alignment with business goals. Develop and maintain data architectures and pipelines to support data analysis and decision-making. Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives. Collaborate with cross-functional teams to understand data needs and provide actionable insights. Ensure data quality and integrity through regular audits and validation processes. Mentor and guide junior data engineers, fostering a culture of continuous learning and improvement. Must be a self-starter, 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 lifecycle—spanning data engineering, architecture, and analytics—to 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. 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. 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 12+ years of experience in enterprise data management, with deep expertise across disciplines including data governance, data architecture, and more. Experience with data management and governance tools and technologies Experience with enabling data products within large organizations Proven experience independently developing and implementing recommended approaches to complex/ambiguous problems while making thoughtful trade-offs Deep understanding and hands-on experience in data platforms Strong technical acumen, being able to quickly understand technical details of a product or platform Strong execution skills-ability to deliver results Comfortable working in a fast-paced, results-oriented environment Shows initiative and exhibits a “can-do” attitude Demonstrated willingness to be flexible and adaptable to changing priorities with the ability to motivate in a cross-functional organization Able to see the “big picture”-the end-to-end connection points associated with data and systems Exhibit a passion for Data Management and Analytics Familiarity with AI/ML pipelines or AI-enhanced data systems (data discovery, data quality monitoring, or integrating ML into ETL flows) Passion for bridging the gap between data engineering and machine learning engineering. Experience enabling ML/AI workloads, such as building feature stores, training data pipelines, or model monitoring infrastructure. Experience in financial services, with a strong preference for exposure to the credit risk domain. BS or advanced degree in Engineering, Computer Science, or related technical field.

Responsibilities

Lead and manage data engineering projects while ensuring alignment with business goals. Collaborate with cross-functional teams to analyze complex datasets and provide actionable insights.