<p>JobID: 210602034</p> <p>Category: Data Engineering</p> <p>JobSchedule: Full time</p> <p>Posted Date: 2025-05-13T18:18:36+00:00</p> <p>JobShift:</p> <p>:</p> <p>Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.</p> <p>As a Data Engineer III at JPMorgan Chase within the Cybersecurity Technology Resilience department, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.</p> <p>As a Data Engineer III in Cybersecurity Technology Resilience, you will utilize your skills to develop and maintain data pipelines and architectures. Your role is vital in ensuring the resilience of our data infrastructure, collaborating with various teams to align with strategic goals, and safeguarding essential business services.</p> <p>Job responsibilities</p> <ul> <li>Supports review of controls to ensure sufficient protection of enterprise data </li><li>Advises and makes custom configuration changes in one to two tools to generate a product at the business or customer request </li><li>Updates logical or physical data models based on new use cases </li><li>Utilize SQL and understands NoSQL databases and their niche in the marketplace </li><li>Manage & optimize databases for performance and efficiency. </li><li>Design & build data pipelines that clean, transform, and aggregate data from disparate sources. </li><li>Develop new models that can be used to make predictions and answer questions for the overall business. </li><li>Contribute to a team culture that values diversity, equity, inclusion, and respect. </li></ul> <p>Required qualifications, capabilities, and skills</p> <ul> <li>Formal training or certification on data engineering concepts and 3+ years applied experience. </li><li>Experience across the data lifecycle </li><li>Advanced at SQL (e.g., joins and aggregations) </li><li>Experience with data structures, such as NoSQL, OTF, and RDMS. </li><li>Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis </li><li>Experience customizing changes in a tool to generate product </li><li>Experience with various database technologies, such as MySQL, PostgreSQL, and MongoDB. </li><li>Experience with analytics engines/platforms, such as Apache Spark and Hadoop. </li><li>Experience with data migration and mapping complex relational data between business systems. </li></ul> <p>Preferred qualifications, capabilities, and skills</p> <ul> <li>Degree, or equivalent practical experience, in Computer Science, Information Systems, Data Science, or a related field. </li><li>Exceptional analytical skills with the ability to translate business requirements into data engineering solutions. </li><li>Experience of data science methods including statistical and analytical techniques. </li><li>Experience in Data Mining techniques used in data science and data analytics. </li><li>Excellent problem-solving abilities, attention to detail, and ability to work independently or in a team. </li><li>Effective communication and interpersonal skills to foster relationships with stakeholders at all levels. </li><li>Advocate for driving efficiencies, stabilization, and continuous improvement. </li></ul>