GCP Data Engineer

About the Role

We are looking for a highly skilled and passionate Big Data Engineer with strong expertise in Java,

Spring Boot, PySpark, and Google Cloud Platform (GCP). The ideal candidate will play a key role in

designing, developing, and maintaining scalable data processing solutions and cloud-native

applications that support large-scale customer personalization and marketing platforms.

You will work with modern data engineering technologies, build high-performance microservices, and

contribute to the migration and modernization of big data workloads on Google Cloud.

Key Responsibilities

Design, develop, and maintain scalable microservices using Java and Spring Boot.

Build and optimize large-scale data processing pipelines using PySpark, BigQuery, and

DataProc.

Migrate existing Hadoop, Spark, and Hive workloads to Google Cloud Platform (GCP).

Develop and maintain RESTful APIs and cloud-native applications.

Write efficient and optimized SQL queries for large datasets.

Collaborate with cross-functional teams to gather requirements and translate them into

technical solutions.

Participate in code reviews, testing, troubleshooting, and continuous improvement initiatives.

Support deployment, monitoring, and maintenance of applications across development, testing,

and production environments.

Contribute to Agile ceremonies and ensure timely delivery of high-quality software.

Required Skills & Qualifications

Bachelor's degree in Computer Science, Engineering, or a related technical discipline.

69 years of software development and data engineering experience.

Strong hands-on experience in Java and Spring Boot.

Solid understanding of Java Collections, Multithreading, and core Java concepts.

Extensive experience with PySpark, Spark, and distributed data processing.

Strong expertise in BigQuery, DataProc, and Google Cloud Platform (GCP).

Proficiency in SQL and database optimization techniques.

Experience designing and developing RESTful APIs and microservices.

Hands-on experience with Hadoop, Hive, and large-scale data platforms.

Strong scripting skills in Python, Shell, or Perl.

Familiarity with Agile development methodologies and CI/CD practices.

Experience troubleshooting and optimizing performance in distributed systems.

What We Look For

Strong problem-solving and analytical skills.

Excellent communication and stakeholder management abilities.

Ability to work independently in a fast-paced environment.

Passion for building scalable, high-performance cloud and data engineering solutions.

Ownership mindset with a focus on quality and continuous improvement.

Key Technologies

PySpark | BigQuery | DataProc | GCP | SQL | AirFlow | Composer..