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Senior Executive Director of Software Engineering - Data Platforms | Workforce and Experience Technology (WXT)
senior · Technology / Software Development
You will be poised to achieve extraordinary success and make a high impact on those around you through data solutions. Partner with an organization comprised of the industry’s thought leaders and committed to advancing your leadership career.
As a Senior Director of Software Engineering at JPMorganChase within the Employee Platforms, Workforce Experience Technology (WxT) Workforce Data and Analytics (WDA) team, you lead multiple technical areas, manage the activities of multiple departments, and collaborate across technical domains. Your expertise is applied cross-functionally to drive the adoption and implementation of technical methods within various teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances You will lead data engineering and drive impact within teams, technologies, and data product offerings across HR, Employee Experience, CAO and EP technology. Utilize your in-depth engineering knowledge and impact for data, analytics, applications, technical processes, and product management to lead multiple complex designs and initiatives making key decisions for your team, and drive innovation and solution delivery.
Job responsibilities
- Builds data pipeline and architecture solutions that can be leveraged across multiple businesses that are easily augmented, exchanged, rotated, etc.
- Champions proficiency in all aspects of the data production pipeline ensuring they are driven by x-as-Code (extraction, transformation, reconciliation, data quality (business, technical), security).
- Utilizes best practice trends in both test-driven and data-driven development.
- Creates modular designs that can be auto repeatable as frameworks to build a data production factory, minimizing ad hoc data generation.
- Leads data engineering scrum teams to achieve functional technology objectives while influencing peer leaders and senior stakeholders across the business, product, and data technology teams
- Partners with Product and Architecture to make strategic decisions that influence teams’ resources, budget, tactical operations, and the implementation of processes and procedures.
- Executes at code level accountability for SDLC, design patterns and upskilling engineers
- Uplifts and modernizes data platforms driving Stability, Timeliness, Completeness, Quality (TDQ/BDQ), Security, FinOps, Operational Excellence and Ease of consumption.
- Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations.
- Champions the firm’s culture of diversity, equity, inclusion, and respect
- Transforms traditional HR/EX into modern data product offerings that scales for business needs.
Required qualifications, capabilities, and skills.
- Formal training or certification on Data Engineering concepts and 12+ years applied experience. In addition, 8+; years of experience leading technologists and software engineers to manage, anticipate and solve complex technical items within your domain of expertise.
- Hands-on Data Engineering development, testing, automation
- Practical experience with the following key technical skills including Databricks, DBX, PySpark, Spark, Cloud Providers: Databricks, AWS, Azure, Terraform, Kafka, Python/Scala, Glue/EMR, AI Developer Automation Tools (Unit Test)
- Experience and innovation in AI and Agentic SDLC
- BI Consumption with tools such as: Sigma, Genie, Tableau SaaS
- Ability to manage governance with Unity Catalogue and Data Access with Immuta
- Experience developing and leading cross-functional teams of technologists.
- Experience dealing with internet scale volume and size of data.
- Experience hiring, developing, and recognizing talent.
- Experience leading a product as a Product Owner or Product Manager
- Experience in Big Data technologies handling complex data processing requirements.
- Experience building data pipelines and platforms in cloud (AWS S3, Databricks, GCP, Azure)
Preferred qualifications, capabilities, and skills
- Experience working hands-on at code level
- Prior Financial Services experience is preferred.