Synechron
Synechron
Synechron is a digital transformation consulting firm serving financial services and big tech organizations. Its work spans consulting, design, cloud, data, and engineering, with particular expertise in payments, sustainable finance, blockchain, and artificial intelligence. With a global team of more than 14,000 professionals, Synechron supports clients seeking to modernize technology, develop digital products, and respond to change across the financial services sector.

GCP Big Data Engineer at Synechron — Python, Spark, Bengaluru Onsite

Build secure, scalable data pipelines for Synechron’s enterprise analytics platforms. Use GCP, Spark, Python, and ETL/ELT technologies to deliver reliable data solutions.

Description

  • Architect and optimize scalable data pipelines and management solutions on GCP
  • Build and maintain resilient pipelines for enterprise analytics and reporting
  • Partner with stakeholders, data scientists, and analytics teams to improve workflows
  • Apply data quality, security, governance, encryption, access control, and compliance practices
  • Improve ingestion, transformation, and processing for performance and cost efficiency
  • Profile data, troubleshoot pipeline failures, and resolve operational issues
  • Automate workflows, manage infrastructure as code, and support deployment pipelines
  • Document architectures, workflows, procedures, and operational guidance
  • Contribute to sprint planning, reviews, and continuous improvement
  • Track data engineering practices and lead initiatives that improve delivery

Requirements

  • Extensive experience with GCP services such as BigQuery, Dataflow, Cloud Storage, and Cloud Pub/Sub
  • Strong Apache Spark skills for distributed data processing and analytics
  • Practical experience building and maintaining ETL/ELT data pipelines
  • Proficiency in Python for scripting, automation, and orchestration
  • Experience managing distributed data stores including PostgreSQL, MySQL, and MongoDB
  • Familiarity with Git
  • Working knowledge of Linux and Unix environments
  • Preferred experience with data governance, metadata management, and data security
  • Preferred knowledge of Apache Airflow or Prefect
  • Preferred understanding of Docker and Kubernetes
  • At least five years of practical data engineering experience focused on GCP and Big Data ecosystems
  • Experience designing and delivering end-to-end data pipelines and workflows at scale
  • Demonstrated expertise in distributed processing, data security, and infrastructure automation
  • Experience contributing to agile teams that support enterprise or large-scale data platforms
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, or a related discipline
  • Extensive experience with Hadoop, Spark, Dataflow, and other GCP or Big Data processing frameworks
  • Ability to create robust, scalable, and secure pipelines for enterprise analytics
  • Strong analytical and problem-solving abilities in distributed data environments
  • Clear communication and effective collaboration skills
  • Leadership ability to promote best practices and mentor junior team members
  • Strategic thinking combined with effective time management

Benefits

  • Flexible workplace options
  • Mentorship opportunities
  • Internal career mobility
  • Learning and professional development programs

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