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Target
Target

Retail company.

Engineer at Target

RoleBackend
LevelMid Level
LocationBangalore, India
WorkOn-site
TypeFull-time
Posted1 day ago
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About the role

About us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

About the role:

L4 Engineer who bring 2+ years of experience should demonstrates strong foundational technical skills, with the ability to implement components of solutions within established frameworks while continuously learning and adapting to new technologies. In this role, they are expected to write clean, testable, and secure code, contribute to debugging and problem-solving, and apply knowledge of systems such as databases, networking, and CI/CD pipelines.

The ideal candidate understands the importance of automated testing, observability, and system reliability, and contributes to these areas with guidance. They work independently on most tasks, take accountability for deliverables, and collaborate effectively within the product team while knowing when to seek support.

Success in this role requires a growth mindset, openness to feedback, and a proactive approach to learning and improving both technical and team practices. The engineer should understand how their work aligns with broader business goals and contribute meaningfully to team outcomes through consistent execution and quality-focused development.

Required Skills

  • Strong proficiency in Java (17+)
  • Experience designing and building microservices architectures
  • Hands-on experience with Spring Boot and other JVM-based frameworks
  • Experience with messaging systems such as Kafka or RabbitMQ
  • Solid understanding of databases, including:
  • NoSQL (e.g., Cassandra, MongoDB)
  • SQL (e.g., PostgreSQL)
  • Experience building and managing CI/CD pipelines (Jenkins, GitLab etc..)
  • Proficiency in unit and integration testing (JUnit, Test Containers)
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Familiarity with monitoring and observability tools (Grafana, ELK Stack, Prometheus)
  • Understanding of event-driven architecture and distributed system design patterns
  • Exposure to agentic frameworks and use of LLMs

Preferred Skills

  • Hand on experience using React and typescript
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Working knowledge of Python
  • Experience designing and integrating GraphQL APIs
  • Knowledge of security best practices and secure coding
  • Familiarity with Agile methodologies (Scrum, Kanban)
  • Experience integrating AI/LLM capabilities into applications
  • Exposure to AI reliability and automation, including agentic frameworks and use of OpenAI APIs/SDKs
  • Knowledge of IAM

Required skills

Java

Spring Boot

Microservices

Debugging

Automated testing

CI/CD

Observability

System reliability

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About Target

Target

Target

Public

Target Corporation, doing business as Target, is an American retail corporation headquartered in Minneapolis, Minnesota, United States. Target operates retail stores. It is the eighth-largest retailer in the United States and is a component of the S&P 500 Index.

10,001+

Employees

Minneapolis

Headquarters

$78B

Valuation

Reviews

10 reviews

3.7

10 reviews

Work-life balance

3.2

Compensation

2.8

Culture

4.1

Career

3.5

Management

4.0

68%

Recommend to a friend

Pros

Friendly coworkers and great team environment

Flexible scheduling and hours

Supportive and approachable management

Cons

Limited or insufficient hours for part-time staff

Long hours and high stress during peak/holiday seasons

Low pay and non-competitive compensation

Salary Ranges

50 data points

Junior/L3

Mid/L4

Lead

Director

Junior/L3 · Decision Sciences Analyst

1 reports

$104,000

total per year

Base

$80,000

Stock

-

Bonus

-

$104,000

$104,000

Interview experience

46 interviews

Difficulty

4.0

/ 5

Duration

21-35 weeks

Offer rate

20%

Experience

Positive 65%

Neutral 21%

Negative 14%

Interview process

1

Recruiter Screen

2

ML Coding

3

ML System Design

4

Research Discussion

5

Team Interviews

Common questions

ML fundamentals

Design an ML system

Research paper discussion

Statistical concepts