Data Engineer

Apply only if you have 5+ years of experience

Required:

Bachelor's degree in computer science, Information Technology, or equivalent

experience

5+ years of experience in software development, with experience in Java / JEE

development

4+ years of hands-on experience with Apache Spark and Scala, including building and

optimizing large-scale batch data processing pipelines.

Proven experience with Amazon EMR, including configuration, tuning, and

orchestration of Spark jobs in a cloud environment.

2+ years of hands-on experience in developing applications for Cloud (AWS, Azure)

Proficiency with SQL & NoSQL Databases (e.g. PostgreSQL and

Couchbase/DocumentDB). Should have working experience in optimizing SQL queries

for application performance.

Working experience of building distributed systems using Pub/Sub, streaming

platforms like Kafka.

Experience with Performance Tuning applications

Working knowledge of DevOps tools such as Git, JIRA, Harness/Jenkins & CICD

Strong communication skills

Preferred :

Experience with enterprise integration patterns, e.g Apache Camel.

Experience with Microservice development and architectures (Java, SpringBoot, JPA,

Hibernate, OSE / K8s)

Experience with ReactJS or a similar JavaScript framework

Experience working with highly concurrent distributed systems, e.g Akka based

applications.

Experience in travel or lodging applications, services, or operations

Enterprise or solution architecture experience

Experience in Agile methodology

Core work activities:

Design, develop, and maintain high-performance Spark and Scala-based data

processing applications on Amazon EMR.

Ensure performance and responsiveness of applications

Design and develop APIs

Stay abreast of developments in web applications and programming languages

Collaborate with architects, engineers, and business teams to design and evolve

architectures and technical solutions

Take technical leadership of software development on a small team and own projects

from inception to delivery

Release high-quality code early and often using lean and agile technical practices and

processes

Promote best practices such as automated testing, code reviews, pair programming,

test-driven development, and continuous integration

Coordinate with Operations and Infrastructure Delivery teams for deployment and

production support activities