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Lead Software Engineer – Data Engineer with Pyspark AWS SQL
Hyderabad, Telangana, India, IN
·
On-site
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Full-time
·
2w ago
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Manager of Software Engineer at JPMorgan Chase within the Technology Division, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities :
- Manage data integration and data analysis of disparate systems
- Build extensible data acquisition and integration solutions to meet the functional and non-functional requirements of the client
- Implement processes and logic to extract, transform, and distribute data across one or more data stores from a wide variety of sources
- Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs
- Interface with other internal product development teams as well as cross functional teams (Product Management, Integration Engineering, Quality Engineering, System Admin Teams)
- Working with remote and geographically distributed teams to enable building the right products, using the right building blocks, and making them consumable by other products easily
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands on experience in data integration projects using Big Data Technologies
- Hands on experience with a minimum of 5 years on Spark and Scala along with experience on building streaming applications using Kafka
- Strong experience in CICD using Jenkins, Git, Artifactory, Yaml, Maven for Cloud deployments
- Java opensource, API, JUnits, Spring Boot applications, Swagger Setup
- Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala- Strong experience in integrating data from different types of file-storage formats like Parquet, ORC, Avro, Sequence files etc.
- Strong technical understanding in building scalable, high performance distributed services/systems
- Strong knowledge of Data Warehousing and Data Lake concepts ; Possesses strong problem solving, troubleshooting, and analytical skills
- Having excellent communication, presentation, interpersonal, and analytical skills including the ability to communicate complex concepts clearly to different audiences
- Experience in technologies like Oracle/SQL and NoSQL data stores such as DynamoDB
Preferred qualifications, capabilities, and skills:
- Experience in AWS Data Warehousing and database platforms preferred
- Ability to quickly learn new technologies in a dynamic environment
- Experience in managing team of at least 5-10 engineers.
- Big data experience preferably related to human resources analytics
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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%
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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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