[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All JPMorganChase jobs](https://jobs.opennash.com/companies/jpmorganchase/) · [Search jobs](/search/) JPMorganChase · Columbus, OH # Lead Data Engineer - ETL Java AI Columbus, OH, United States Manager or lead Data & Analytics Listed on JPMorganChase’s official careers site. Posted October 15, 2026. Check that it is still open and apply there. [Apply on JPMorganChase’s careers site →](https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210787320) [OpenNash Jobs](https://jobs.opennash.com/) / [JPMorganChase](https://jobs.opennash.com/companies/jpmorganchase/) / Lead Data Engineer - ETL Java AI ## Job description We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Marketing Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. ### Job responsibilities - Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems - Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. - 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 - Lead architecture and hands-on delivery of large-scale data pipelines (ETL/ELT) covering ingestion, transformation, validation, reconciliation, and publishing across curated layers - Design and operationalize data lake patterns, including partitioning strategies, data quality controls, lineage, governance, and reusable datasets/data products - Build and optimize distributed processing workloads using Apache Spark and modern storage/file formats (e.g., Parquet, Avro) - Drive performance tuning across compute and storage (e.g., Spark tuning: shuffle, joins, caching, skew handling; and warehouse tuning where applicable) ### Implement engineering best practices code quality, automated testing, CI/CD, observability (metrics/logs/traces), security-by-design, and operational readiness - Build and maintain Java-based services and components that support data workflows (e.g., ingestion services, orchestration helpers, APIs, data access layers) Develop REST APIs and integration components to enable downstream consumption and platform interoperability - Apply modern application engineering practices (clean architecture, SOLID principles, test automation, and secure coding practices) Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience - Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. - Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices - 10+ years of software engineering experience, with strong depth in data engineering/big data platforms - Strong hands-on development experience in Java plus proficiency in at least one data-focused language such as Python - Proven experience designing and building robust ETL/ELT pipelines and data integration frameworks - Strong experience with Apache Spark and distributed processing concepts (fault tolerance, partitioning, performance tuning) - Strong understanding of data storage serialization and formats such as Parquet and Avro - Solid knowledge of data lake/lakehouse concepts and patterns (e.g., Medallion architecture), including data quality, metadata, and governance considerations Experience working with cloud data warehouses such as Snowflake (loading/unloading patterns, performance basics) or equivalent - Ability to lead technical discussions, communicate clearly to varied stakeholders, and drive delivery in cross-functional environments Preferred qualifications, capabilities, and skills Experience with orchestration and workflow scheduling tools (e.g., Airflow, Dagster, Control-M, etc.) Exposure to streaming/event-driven processing (e.g., Kafka, Spark Structured Streaming) and incremental processing patterns (CDC, upserts) Experience with table formats / ACID layers (e.g., Delta Lake, Apache Iceberg, Hudi). Strong production operations mindset (on-call practices, SLAs/SLOs, observability, incident response). Experience in regulated environments (risk, audit, compliance, privacy, PII handling). Experience with cost optimization / FinOps practices for data platforms. Experience with working with Agentic AI / Gen AI solutions and capabilities will be an added advantage. ## At a glance - Posted by the employer: Oct 15, 2026 - First seen by OpenNash: Oct 13, 2026 - Last checked: Oct 20, 2026 - Listed for: 7 days - Location: Columbus, OH, United States[Apply on JPMorganChase’s careers site →](https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210787320) ## More jobs at JPMorganChase ### [2027 Focused Analytics Solutions Team (FAST) Intern Associate Program – Analytics Solutions](https://jobs.opennash.com/companies/jpmorganchase/jobs/8e2a6440d6e71c576cad/) Columbus, OH, United States ### [Analytics Strategy Lead-Vice President](https://jobs.opennash.com/companies/jpmorganchase/jobs/3fb2b5a10c1b17e2886c/) Columbus, OH, United States ### [Applied AI ML-Senior Associate](https://jobs.opennash.com/companies/jpmorganchase/jobs/23146fbf5790fab050ed/) Columbus, OH, United States ### [Business Banking Data Owner Lead - Insurance](https://jobs.opennash.com/companies/jpmorganchase/jobs/75b592b652688eb55137/) Columbus, OH, United States ### [Business Banking Data Owner Senior Associate - Insurance](https://jobs.opennash.com/companies/jpmorganchase/jobs/c1f809d9d1207718aa80/) Columbus, OH, United States ## Similar jobs at other companies ### [Lead ETL Developer- Enterprise Data Warehouse (EDW)](https://jobs.opennash.com/companies/huntington-bank/jobs/6409cc74b43788596a02/) Huntington Bank · Dallas, TX Columbus, OH Minnetonka, MN ### [QA Test Automation Lead - Data Warehouse & ETL](https://jobs.opennash.com/companies/huntington-bank/jobs/0ca1f5bd9c89626020e5/) Huntington Bank · Hoover, AL Cincinnati, OH Dallas, TX Columbus, OH Houston, TX Minnetonka, MN Tupelo, MS ### [The Core Engineering-Compliance, Senior Backend Engineer (Java & ETL Specialist), Vice President, Dallas](https://jobs.opennash.com/companies/goldman-sachs-group/jobs/c19a1942a41c31086ea9/) Goldman Sachs Group · Dallas, United States ### [ETL Java Developer](https://jobs.opennash.com/companies/leidos/jobs/208bee6fb63b113dc757/) Leidos · Bethesda, MD ### [ETL Java Developer (SME)](https://jobs.opennash.com/companies/leidos/jobs/423164f59e9ff6b2cd8e/) Leidos · Bethesda, MD OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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