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Chase · 4 hours ago

Software Engineer III – Big Data & Analytics

1111 Polaris Pkwy, Columbus, OH, 43240, US

Full-time

Onsite

Mid Level

3+ years exp

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. As a Software Engineer for Big Data and Analytics, you will be an integral part of an agile team that delivers critical technology solutions across multiple technical areas and business functions.

BankingFinancial Services

Responsibilities

Oversee all aspects of data strategy, governance, data risk management, reporting, and analytics

Manage risks associated with data use, retention/destruction, and privacy

Design, develop, code, test, debug, and deploy scalable and extensible applications

Produce high-quality code utilizing Test Driven Development techniques

Participate in retrospectives to drive continuous improvement within the feature team

Participate in code reviews, ensuring all solutions align with pre-defined architectural specifications

Implement automation through Continuous Integration and Continuous Delivery

Manage cloud development and deployment, supporting applications in both private and public clouds

Qualification

JavaAWSPythonSparkScalaSQLData WarehousingData EngineeringETL TechnologyAgile FrameworkProcess ImprovementData ModelingMachine LearningCollaboration Skills

Required

Formal training or certification in software engineering concepts and 3+ years of applied experience

Advanced knowledge of architecture, design, and business processes

Full Software Development Life Cycle experience within an Agile framework

Expert-level skills in Java, AWS, database technologies, Python, Scala, Spark/PySpark, or any ETL technology

Experience developing and decomposing complex SQL on RDMS platforms

Experience with Data Warehousing concepts (including Star Schema)

Practical experience delivering projects in Data and Analytics, Big Data, Data Warehousing, and Business Intelligence; familiarity with relevant technological solutions and industry best practices

Strong understanding of data engineering challenges and proven experience with data platform engineering (batch and streaming, ingestion, storage, processing, management, integration, consumption)

Familiarity with multiple Data & Analytics technology stacks

Awareness of various Data & Analytics tools and techniques (e.g., Python, data mining, predictive analytics, machine learning, data modeling, etc.)

Experience with one or more leading cloud providers (AWS, Azure, GCP)