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Chase · 3 hours ago

Lead Software Engineer - DataBricks / PySpark

1111 Polaris Pkwy, Columbus, OH, 43240, US

Full-time

Onsite

Senior Level, Lead/Staff

5+ years exp

JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. As a Lead Software Engineer within the Corporate Technology Workforce Data Analytics team, you will enhance and deliver technology products while implementing critical solutions to support various business functions.

BankingFinancial Services

Responsibilities

Execute creative data solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems

Develop secure high-quality production data pipelines, and review and debug data processes implemented by others

Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of data applications and systems

Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Lead communities of practice across Data Engineering to drive awareness and use of new and leading-edge technologies

Contribute to a team culture of diversity, opportunity, inclusion, and respect

Qualification

Data EngineeringPythonPySparkAWSDatabricksAutomationAgile methodologiesSoftware Development Life CycleCloud-native experienceFinancial services knowledgeUnity CatalogDelta tablesIceberg tablesParquetCI/CDApplication ResiliencySecurityMachine learningArtificial intelligenceMobileTechnical troubleshooting

Required

Formal training or certification on software engineering concepts and 5+ years applied experience

3+ years of experience in Data Engineering, specifically design, application development, testing and operational stability in Python, PySpark, Glue, Lambda, Databricks and AWS

Knowledge of Unity Catalog, data formats including Delta tables, Iceberg tables

Hands-on practical experience delivering system design, application development, testing, and operational stability

Advanced proficiency in data processing frameworks and tools, including knowledge in Parquet and Iceberg

Proficiency in automation and continuous delivery methods

Proficient in all aspects of the Software Development Life Cycle

Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Demonstrated proficiency in data applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

In-depth knowledge of the financial services industry and their IT systems

Practical cloud-native experience