GCP Data Engineer | Java & PySpark

Posted 23 Days Ago
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Gurugram, Haryana, IND
In-Office
6-6 Annually
Senior level
Fintech • Financial Services
The Role
The Data Engineer will develop and maintain microservices and data pipelines using GCP technologies, collaborate with Agile teams, and address business requirements by delivering scalable data-driven solutions.
Summary Generated by Built In

Job Summary
Synechron is seeking a highly skilled GCP Data Engineer with expertise in Java and PySpark to lead the development of scalable data pipelines and microservices on Google Cloud Platform. In this role, you will collaborate with cross-functional teams to design, implement, and optimize data-driven solutions that support our global marketing and personalization initiatives. Your technical leadership will enable innovative cloud-native architectures that enhance business capabilities and drive operational efficiency.

Software Requirements
 

Required Software Proficiency:

  • Java (preferably version 8 or newer) — extensive experience in developing backend services using Java and Spring Boot

  • PySpark — proven experience in large-scale data processing within GCP environments

  • SQL — hands-on experience with relational databases and query optimization techniques

  • Google Cloud Platform (GCP): DataProc, BigQuery, GKE, Cloud Storage — solid working knowledge of deploying and managing data systems on GCP

  • UNIX/Linux shell scripting, Python, Perl — practical knowledge in scripting for automation and data manipulation

  • RESTful web services — experience in designing and implementing APIs for data exchange

  • Version control: Git — strong familiarity with code management and collaboration workflows

Preferred Software Skills:

  • GCP-native tools: Dataflow, Cloud Composer, Cloud Storage — experience with fully managed cloud data workflows

  • Hadoop, Hive, or additional big data processing tools — for data migration and legacy system integration

  • Machine learning libraries: TensorFlow, Scikit-learn — knowledge for implementing AI/ML features

  • Data streaming tools: Kafka — experience with real-time data pipelines and event processing

Overall Responsibilities

  • Design, develop, and optimize large-scale data pipelines leveraging PySpark, DataProc, and BigQuery, ensuring robustness and scalability

  • Build and maintain microservices and APIs using Java (Spring Boot), deployed on GKE (Google Kubernetes Engine)

  • Collaborate with product teams, data scientists, and stakeholders to analyze data requirements and translate into technical solutions

  • Modernize architecture by migrating workloads from Hadoop, Spark, and Hive to GCP cloud infrastructure

  • Conduct performance tuning, troubleshooting, and system optimization for data pipelines and services

  • Write detailed technical documentation, including architecture diagrams, APIs, and deployment procedures

  • Stay informed on emerging trends in cloud data engineering, AI/ML, and big data to apply innovations effectively

  • Lead code reviews, enforce coding standards, and foster best practices across the team

Technical Skills (By Category)

  • Programming Languages:

    • Essential: Java (Spring Boot), PySpark, SQL — proven ability to develop scalable backend and data processing solutions

    • Preferred: Shell scripting, Perl, Python — for automation and scripting tasks

  • Databases/Data Management:

    • BigQuery, DataProc, Hadoop, Hive — experience in designing, managing, and optimizing large datasets and query performance

  • Cloud Technologies:

    • GCP (DataProc, BigQuery, GKE, Cloud Storage) — thorough knowledge of cloud deployment, data integration, and management

  • Frameworks & Libraries:

    • PySpark, Dataflow for data processing; REST API development with Spring Boot

  • Development Tools & Methods:

    • Git, CI/CD pipelines (Jenkins, Cloud Build), Agile/scrum practices for collaboration and continuous deployment

  • Security & Data Governance:

    • Understanding of data security, privacy standards, and best practices for cloud-based data platforms

Experience Requirements

  • 4+ years of professional experience in data engineering, software development, or related roles, preferably on cloud platforms

  • Demonstrated experience developing and deploying scalable data pipelines and microservices in GCP environment

  • Proven expertise in Java and PySpark for large data processing and system integration

  • Familiarity with cloud migration projects, big data frameworks, and AI/ML libraries is a plus

  • Effective in collaborative, agile team environments with a focus on delivering results

Day-to-Day Activities

  • Develop, test, and refine data pipelines using PySpark, DataProc, and BigQuery

  • Design and implement scalable back-end microservices and APIs with Java Spring Boot, deployed on GKE

  • Participate in Agile ceremonies, including sprint planning, stand-ups, and reviews

  • Monitor system performance, troubleshoot issues, and optimize data workflows for efficiency and reliability

  • Collaborate with data scientists, product managers, and analysts to deliver data-driven features

  • Document system architecture, data models, and deployment instructions to ensure maintainability

  • Continuously explore new cloud, big data, and AI/ML tools to improve infrastructure and solutions

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field

  • 4+ years of experience in data engineering, big data processing, or software development, with strong cloud expertise

  • Certifications such as GCP Professional Data Engineer are advantageous

  • Proven ability to design scalable solutions and lead data migration projects on cloud platforms

Professional Competencies

  • Strong analytical and problem-solving skills for designing optimized data pipelines

  • Leadership capabilities to manage project goals and mentor junior team members

  • Excellent communication skills for translating technical solutions to stakeholders

  • Adaptability and eagerness to explore cutting-edge technologies and methodologies

  • Results-driven, with a focus on delivering reliable, scalable, and innovative data solutions

  • Effective time management to prioritize workload and meet project deadlines

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Candidate Application Notice

Skills Required

  • Minimum 6 years of relevant experience in software and data engineering roles
  • Bachelor's degree in Computer Science, Engineering, or a related technical discipline
  • Experience with Java, Spring Boot, SQL, and cloud-based data tools on GCP
  • Experience with JSON, REST APIs, and microservices architecture
  • Certifications in GCP (such as GCP Professional Data Engineer)

Synechron Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Synechron and has not been reviewed or approved by Synechron.

  • Fair & Transparent Compensation Pay is frequently characterized as competitive, particularly relative to large service-consulting peers and in certain in-demand skill areas. Compensation sentiment appears strongest when staffing is stable on strong client engagements and for market-aligned roles in major hubs.
  • Healthcare Strength Healthcare coverage is often portrayed as a strong point in the U.S., with broad coverage and relatively favorable out-of-pocket experiences. Core medical, dental, and vision options are consistently described as meeting or exceeding a baseline expectation for consulting roles.
  • Equity Value & Accessibility Equity was made broadly accessible through a company-wide RSU grant tied to a major revenue milestone. This is positioned as a notable upside even if it is framed as a one-time recognition event rather than an ongoing program.

Synechron Insights

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The Company
Maharashtra
12,827 Employees
Year Founded: 2001

What We Do

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,700+, and has 48 offices in 19 countries within key global markets. For more information on the company, please visit our website: www.synechron.com.

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