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AWS Big Data Lead Software Engineer

JPMorgan Chase

AWS Big Data Lead Software Engineer

JPMorgan Chase

Columbus, OH, United States, US

·

On-site

·

Full-time

·

2w ago

Job responsibilities

  • Design & build new applications utilizing leading edge technologies and modernize existing applications
  • Implement batch & real-time software components consistent with architectural best-practices of reliability, security, operational efficiency, cost-effectiveness and performance
  • Ensure quality of deployed code via automated unit, integration & acceptance testing
  • Collaborate with multi-national agile development, support and business teams to meet sprint objectives
  • Participate in all agile meetings & rituals, including daily standups, sprint planning, backlog reviews, demos, and retrospectives
  • Provide level 2 support for production systems
  • Learn and applies system processes, methodologies, and skills for the development of secure, stable code and systems
  • Hands on applicaitn development leveraging distributed compute such as Apache flink or Spark on very large datasets
  • Design and development of applications that leverage the AWS infrastructure deploying software components on AWS using common compute and storage services such as EC2, EKS, Lambda, S3
  • Lead and deliver projects from concept to production across PNI (Personalization and Insights) platform

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience in Frameworks, system design, application development, testing, and operational stability
  • Experience with Apache Spark, Apache Flink or similar large-scale data processing engines
  • Experience with Distributed Datastores (e.g. Cassandra, Red Shift)
  • Experience designing, developing and deploying software components on AWS using common compute and storage services such as EC2, EKS, Lambda, S3
  • Experience with Big Data / Distributed / cloud technology (AWS Big data services like lambda, glue, glue emr, Performance tuning, Streaming, KAFKA, Entitlements etc., )
  • Experience with Apache Spark, Ray or similar large-scale data processing engines
  • Proficiency in automation and continuous delivery methods
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, Big Data, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities, and skills

  • Experience building ETL/Feature processing pipelines
  • Experience using workflow orchestration tools—Airflow, Kubeflow etc.
  • Experience using Terraform to deploy infrastructure-as-code to public cloud
  • Experience with Linux scripting such as Bash, KSH, or Python
  • Certified AWS Cloud Practitioner, Developer or Solutions Architect strongly preferred

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About JPMorgan Chase

JPMorgan Chase

JPMorgan 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