What are the responsibilities and job description for the Director of Data Engineering, Workforce position at JPMorgan Chase?
You are poised to achieve extraordinary success and make a high impact on those around you. Partner with an organization comprised of the industry’s thought leaders and committed to advancing your leadership career.
As a Director of Data Engineering at JPMorgan Chase within the Employee Platforms, Workforce Data and Analytics team, you lead data engineering and drive impact within teams, technologies, and data product offerings across HR, Employee Experience, CAO and EP. Utilize your in-depth engineering knowledge and impact for data, analytics, applications, technical processes, and product management to lead multiple complex projects and initiatives, make key decisions for your team, and a drive innovation and solution delivery.
Job responsibilities
- Delivers data pipeline and architecture solutions that can be leveraged across multiple businesses that are easily augmented, exchanged, rotated, etc.
- Proficient in all aspects of the data production pipeline are driven by x-as-Code (extraction, transformation, reconciliation, data quality (business, technical), security). Trends in both test-driven and data-driven development.
- Modular designs that can be auto repeatable as frameworks.
- Lead to build a data production factory, minimizing ad hoc data generation.
- Leads data engineering scrum team to achieve functional technology objectives.
- Makes strategic decisions that influence teams’ resources, budget, tactical operations, and the implementation of processes and procedures.
- Execution level accountability for SDLC, design patterns and upskilling engineers
- Uplift and modernize 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.
- Influences peer leaders and senior stakeholders across the business, product, and data technology teams. Champions the firm’s culture of diversity, equity, inclusion, and respect
- Transform 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, 5 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
- Key Technical Skills:
- Cloud Providers: AWS, Data Bricks, Azure
- Glue/EMR/DBX
- Terraform
- Apache Spark, Kafka
- Python/Scala
- AI Developer Automation Tools (Unit Test)
- Experience developing and leading cross-functional teams of technologists, dealing with internet scale volume and size of data.
- Experience hiring, developing, and recognizing talent. 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, GCP, Azure)
Preferred qualifications, capabilities, and skills
- Prior banking experience is preferred.
