Overview
Skills
Job Details
Title: Data Engineer III (Offshore/Nearshore - Night Shift)
Location: Offshore/Nearshore Only (NO Onshore)
Work Hours: Must work EST hours 8:00 AM to 5:00 PM or 9:00 AM to 6:00 PM EST (Night Shift for offshore)
Interview Process: 2 Rounds 1 with Hiring Manager, 1 with the Technical Team
Client: [Confidential]
Note: Please confirm availability for EST hours with the candidate before submitting.
Eligible Locations
Offshore: India, Brazil, Costa Rica, Netherlands, Poland, Romania, Hungary
Nearshore: Canada, Mexico
Job Summary
We are seeking a Data Engineer III to join a growing team responsible for designing and optimizing data architecture and data pipelines across critical enterprise initiatives. The ideal candidate will have strong hands-on experience in Java Spring Boot, Kafka, and MongoDB, and must be comfortable working in an Agile environment and supporting cross-functional teams.
This role requires a self-starter with excellent communication skills, capable of working with both technical and non-technical stakeholders.
Must-Have Skills (3 5 Years' Experience)
Java Spring Boot & Microservices
Experience building microservices in a streaming application environment
Strong problem-solving skills and ability to troubleshoot challenges in real-time applications
Apache Kafka
Proficient in message serialization, stream processing, and partitioning
MongoDB
Strong knowledge of data modeling, schema design, and query optimization
Agile Methodologies
Familiar with Scrum, Kanban or similar frameworks
Excellent Communication Skills
Ability to explain complex technical topics to non-technical stakeholders
Nice to Have
Avro Schema experience, especially in managing schema evolution in data pipelines
Sample Interview Questions
Technical:
Describe your experience building microservices using Java Spring Boot.
How have you used Kafka in production environments?
How do you interact with and optimize MongoDB databases?
Methodologies:
What Agile frameworks have you worked with?
How do you contribute to sprint planning and retrospectives?
Communication & Problem Solving:
Share an example where you had to explain a technical issue to a non-technical audience.
Describe a project with ambiguous requirements and how you handled it.
How do you maintain data quality and consistency in your pipelines?
Key Responsibilities
Design, develop, and maintain scalable data pipelines and systems
Collaborate with cross-functional teams to support data initiatives
Optimize and maintain data flow and data collection for enterprise solutions
Handle schema design, data mapping, modeling, and consumption
Drive continuous improvements in performance, scalability, and reliability of the data platform
Tackle complex data engineering problems with minimal guidance
Apply now if you re passionate about data engineering and ready to take ownership of key architectural and pipeline initiatives while working with global teams!