Develop and support scalable data pipelines and enterprise data products using Databricks and distributed data processing technologies. Implement ingestion, transformation, integration, data quality, monitoring, and observability controls. Troubleshoot production issues, contribute to analytical and AI-enabled solutions, and collaborate with engineers, architects, product owners, and business stakeholders. Apply software development lifecycle practices, testing, version control, CI/CD, secure coding, and responsible AI-assisted development.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Commercial & Investment Bank - Digital & Platforms Services team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will help build and support enterprise data products and data platforms that power analytics, reporting, operational, and AI-driven solutions. Working alongside senior engineers, architects, and product teams, you will develop scalable data pipelines, contribute to data product development, and grow your expertise in modern Data Engineering practices.
Job Responsibilities
- Design, develop, test, and support data pipelines and data products using modern Data Engineering practices.
- Build and maintain scalable data ingestion, transformation, and integration processes on Databricks and related platform technologies.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Implement data quality, validation, monitoring, and observability controls to ensure reliable and trusted data.
- Contribute to the development of analytical, operational, reporting, and AI-enabled data solutions.
- Collaborate with engineers, architects, product owners, and business stakeholders to understand requirements and deliver data solutions.
- Troubleshoot data pipeline issues, support production environments, and participate in operational support activities.
- Apply established engineering standards, design patterns, and best practices while continuously improving development skills.
- Participate in code reviews, testing, documentation, and release activities to ensure high-quality delivery.
- Identify opportunities to improve data quality, platform efficiency, automation, and engineering productivity.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Experience working with Databricks and distributed data processing technologies.
- Strong programming skills and understanding of Data Engineering fundamentals.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Familiarity with data architecture concepts, data modeling, and data product principles.
- Experience building and supporting batch and/or real-time data pipelines.
- Strong analytical and problem-solving skills with the ability to troubleshoot technical issues independently.
- Understanding of software development lifecycle practices, testing, version control, and CI/CD concepts.
- Strong communication and collaboration skills with the ability to work effectively in cross-functional teams.
Preferred Qualifications
- Experience working with modern enterprise data platforms and cloud-native data architectures.
- Experience supporting real-time, analytical, or AI/ML-oriented data use cases.
- Experience delivering data solutions within financial services or another highly regulated environment.
- Relevant Databricks, cloud, or Data Engineering certification.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Similar Jobs
Financial Services
Design, build, and optimize end-to-end data pipelines and architectures using Databricks, Spark, AWS, Airflow, and Kafka. Develop ETL processes, data models, warehouses, and reliable Python and SQL solutions while ensuring data quality, security, and governance. Collaborate with data scientists, analysts, and stakeholders to support analytics and AI/ML initiatives. Monitor workflows, troubleshoot issues, validate AI-assisted outputs, and improve performance and resiliency.
Top Skills:
Amazon RedshiftAmazon S3Apache AirflowApache KafkaSparkAWSAws LambdaDatabricksDockerKubernetesPythonSQL
Financial Services
Develops secure, scalable software and data solutions using Python, PySpark, AWS, and Databricks. Designs applications, writes production code, troubleshoots systems, creates architecture artifacts, and analyzes large datasets. Builds and optimizes Spark clusters, validates data quality with SQL, deploys machine learning models, and applies responsible AI-assisted development practices. Collaborates within agile teams to improve application resiliency, security, automation, and operational stability.
Top Skills:
Apache AirflowSparkAws CloudwatchAws Ec2Aws EmrAws S3Ci/CdControl-MDatabricksNumpyPandasPysparkPythonSQL
HR Tech • Information Technology • Professional Services • Sales • Software
Prospects target accounts through outbound calls, email, and other communications to generate new business opportunities. Identifies decision-makers, evaluates buying readiness and timelines, and develops business relationships. Collaborates with Marketing on campaigns, nurtures prospects through the customer journey, and records sales information, data, and metrics. The role requires strong communication, organization, multitasking, creativity, independence, and teamwork.
Top Skills:
HrisLinkedin Sales NavigatorOutreachSaaSSalesforceSalesloft
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
