招聘

Manager of Software Engineering - Data Products
Columbus, OH, United States, US
·
On-site
·
Full-time
·
4mo ago
We have an exciting opportunity to lead a agile team, manage day-to-day implementation activities, hands on coding, and set overall guidance.
As a Manager of Software Engineering at JPMorgan Chase within the Consumer and Community Banking, you will lead multiple teams, overseeing daily implementation activities. Your role involves identifying and escalating issues while ensuring that your team's work aligns with compliance standards, business requirements, and tactical best practices.
Job Responsibilities
- Responsible for all aspects of data strategy, governance, data risk management, reporting and analytics.
- Work with product owners, data owners and customers to evaluate data requirements and identifying right technology solutions and implementation.
- Design, develop, code, test, debug and deploy applications for scalable and extensible applications.
- Product high quality code utilizing Test Driven Development techniques.
- Participate in retrospectives to drive continuous improvement with in the feature team.
- Participate in code reviews and ensuring that all solutions are aligned to pre-defined architectural specifications.
- Implement automation: Continuous integration and continuous delivery.
- Manage cloud development and deployment: support development and deployment of applications into AWS Public clouds.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- advanced knowledge of architecture, design and business processes.
- Full software development life cycle experience within an Agile framework
- Expert level implementation skills with Abinitio, Spark, and Python.
- Experience with the development and decomposition of complex SQL (RDMS platforms)
- Experience with Data Warehousing concepts (including Star Schema)
- Practical experience in delivering projects in Data and Analytics, Big Data, Data Warehousing, Business Intelligence. Familiar with relevant technological solutions and industry best practices.
- Responsible for understanding of data engineering challenges and proven experience with data platform engineering (batch and streaming, ingestion, storage, processing, management, integration, consumption)
- Aware of various Data & Analytics tools and techniques(e.g. Python, data mining, predictive analytics, machine learning, data modelling, etc.)
- Experience with one or more leading cloud providers (AWS/Azure/GCP)
Preferred qualifications, capabilities, and skills
- Ability to work fast and quickly ramp up on new technologies and strategies
- Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals.
- Appreciation of Controls and Compliance processes for applications and data
- In depth understanding of data technologies and solutions is preferable.
- Drive process improvements and implement process changes as necessary.
- Knowledge of industry-wide Big Data technology trends and best practices
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.
300,000+
Employees
New York City
Headquarters
Reviews
4.2
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Work Life Balance
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Pros
Good pay and benefits
Work-life balance
Career advancement opportunities
Cons
Heavy workload at times
Career advancement takes time
Pay could be better in some roles
Salary Ranges
47 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
21 reports
$126,500
total / year
Base
$110,000
Stock
-
Bonus
-
$95,450
$155,250
Interview Experience
4 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Interview Process
1
Application Review
2
HireVue Video Interview
3
Technical/Behavioral Assessment
4
Final Interview Round
5
Offer Decision
Common Questions
Behavioral/STAR
Technical Knowledge
Past Experience
Culture Fit
Case Study
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