Data Engineer III - ETL
About The Position
As a Data Engineer III at JPMorganChase within Corporate Technology, you serve as a seasoned member of an agile team, designing and delivering trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You develop, test, and maintain critical data pipelines and architectures across multiple technical areas and business functions in support of the firm’s business objectives. The role includes supporting enterprise data controls, making requested configuration and customization changes, updating logical or physical data models for new use cases, and using SQL and relevant NoSQL technologies. You also apply enterprise-authorized AI capabilities to support pipeline and design analysis, documentation, testing, and control validation. AI-assisted outputs must be validated, handled according to data sensitivity and security requirements, and kept traceable and auditable in line with resiliency and security expectations.
Requirements
- Formal training or certification in data engineering concepts and at least 3 years of applied data engineering experience, including a track record of developing and deploying business-critical production pipelines.
- Hands-on experience across the data lifecycle building and optimizing ETL/ELT pipelines, including performance tuning, partitioning, file sizing, and incremental loads.
- Proficiency in SQL, including joins, analytics and window functions, and query optimization.
- Experience working with Databricks Genie Spaces and integrating ThoughtSpot with Databricks.
- Strong Oracle experience, including DDL/DML, schema design best practices, and performance tuning using execution plans, indexes, partitioning, and statistics.
- Experience handling JSON and semi-structured data, including parsing, flattening, and schema evolution considerations.
- Proficiency with Git-based workflows using Bitbucket and/or GitHub, and comfort with IntelliJ IDEA or a similar integrated development environment.
- Strong problem-solving and debugging skills across ingestion, transformation, and serving layers.
- Demonstrated experience using enterprise-authorized AI capabilities for data engineering workflows, with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted outputs, such as query suggestions, test ideas, or model change summaries, before use; escalate uncertainty and follow data-handling requirements.
- Experience with statistical data analysis and the ability to determine appropriate tools and data patterns for analysis and customize tools to generate product outputs.
Nice To Haves
- Experience enabling or administering Unity Catalog, including catalog and schema design, permissions management, and lineage and metadata patterns.
- Understanding of data lake, data mesh, and lakehouse architectures.
- Exposure to containerization and orchestration technologies such as Docker or Kubernetes.
- Familiarity with CI/CD tooling and DevOps practices.
- Knowledge of financial services technology or regulated industry environments.
Responsibilities
- Support reviews of controls to ensure sufficient protection of enterprise data.
- Use enterprise-authorized AI capabilities to accelerate data pipeline and design analysis and documentation, validating outputs and following data sensitivity and security requirements.
- Make configuration and customization changes to generate products in response to business or customer requests, and advise colleagues on requests.
- Update logical or physical data models based on new use cases.
- Use SQL frequently and understand NoSQL databases and their role in the marketplace.
- Apply reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines, including test generation and control validation, while ensuring traceability, auditability, resiliency, and security alignment.
- Develop, test, and maintain critical data pipelines and architectures across technical areas and business functions.
Benefits
- Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
- Comprehensive health care coverage.
- On-site health and wellness centers.
- Retirement savings plan.
- Backup childcare.
- Tuition reimbursement.
- Mental health support.
- Financial coaching.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
