Director of Software Engineering - Data and Analytics Services
On-site · Houston, Texas, United States
Job Summary
Director of Software Engineering - Data and Analytics Services at JPMorganChase leads a technical area, drives architecture, strategy, and delivery across teams and domains. Responsibilities include governance over coding decisions and costs of ownership, delivering cross-business technical solutions, influencing senior stakeholders, guiding daily tasks of software engineers, anticipating dependencies, and championing diversity and inclusion while establishing execution plans and outputs. Required capabilities include senior-level software engineering leadership, Java/Python proficiency, cloud proficiency (AWS/Azure/Google Cloud), Databricks data processing, SDLC/CI-CD security, RESTful microservices with Spring Boot, and experience with Kafka/Spark for data processing, plus experience building data pipelines on AWS and experience with data warehouses and modelling.
Required Qualifications
- Formal training or certification on software engineering concepts
- 10+ years applied experience
- 5+ years leading technologists to manage, anticipate and solve complex technical items within your domain of expertise and more broadly across the organization
- Experience leading large feature teams of software engineers to deliver intensive data driven applications
- In-depth knowledge and experience in Java and/or Python, with a strong understanding of scripting, automation, and data analysis
- Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud, including deployment and management of cloud-based applications
- Expertise in data platform technologies, particularly with tools like Databricks, for data processing and analytics
- Proficient in all aspects of the Software Development Life Cycle and advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Strong expertise in building RESTful micro-services using Spring Boot applications
- Experience in Data technologies handling complex data processing requirements-Data streaming and messaging frameworks (e.g. Kafka, Spark Structured Streaming)
- Experience building data pipelines and platforms on AWS
- Development experience on private cloud, public cloud (using EC2, S3, RDS, Lambda, EMR, Step functions, Glue), ETLs and Data Pipeline
- Experience working with large datasets, data warehouses and data modelling
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.