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Software Engineer III - Databricks, SQL , Python
Bengaluru, Karnataka, India, IN
·
On-site
·
Full-time
·
3w ago
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Chief Technology Office team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Our lake house is required to ingest, transform and store additional data sets, that will be used not only to train our AI systems, but also for analytical purposes across multiple use cases. The processing and persistence of data will be managed within the public cloud and will utilise Big Data frameworks such as Databricks and Spark.
We are looking for a Data Engineer to help us with the design, development, deployment, delivery, and maintenance of AI products to our clients. In this role, you will be working with other software and data engineers & research scientists. You will serve as a member of an existing agile team that will deliver trusted market-leading AI technology products in a secure, stable, and scalable way.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities, and skills
- Formal training or certification on Software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Extensive development experience using Python/SQL
- Solid understanding of software applications and technical processes within a related technical discipline (e.g. data ingestion, data storage, data serving, APIs, etc.).
- Hands-on experience in data lake or data warehouse and related technologies (e.g. Spark, ETL, Databricks).
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
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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
10 reviews
Work Life Balance
4.2
Compensation
4.3
Culture
4.5
Career
4.4
Management
4.1
75%
Recommend to a Friend
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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