GCP Big Data Engineer - Python, Spark, Dataflow, BigQuery & ETL/ELT

About the role

Synechron is looking for a highly skilled Data Engineer specializing in Google Cloud Platform (GCP) and Big Data technologies to architect, develop and optimize scalable data pipelines and data management solutions. The role supports enterprise data initiatives, ensuring data quality, security and accessibility for business insights, and works closely with business stakeholders, data scientists and analytics teams.

Key responsibilities

• Design, develop and maintain scalable, resilient data pipelines on GCP for enterprise analytics and reporting
• Work with stakeholders and analytics teams to turn business requirements into optimized data workflows
• Implement and enforce data quality, security and governance standards
• Optimize ingestion, transformation and processing for performance and cost efficiency
• Profile data, troubleshoot and resolve pipeline issues
• Stay current with data engineering best practices and lead continuous improvement
• Automate workflows, manage infrastructure as code, document architecture and procedures, and take part in sprint planning and reviews

Required profile

• 5+ years of practical data engineering experience, focused on GCP and Big Data
• Hands-on experience designing end-to-end data pipelines at scale
• Experience in agile teams supporting enterprise or large-scale data platforms
• Bachelor's or Master's degree in Computer Science, Data Science, IT or a related field
• Experience in finance, healthcare, retail or technology is advantageous

Required skills

• GCP services: BigQuery, Dataflow, Cloud Storage, Cloud Pub/Sub, IAM, Cloud Functions
• Apache Spark and ETL/ELT pipelines
• Python for scripting, automation and orchestration
• Databases: PostgreSQL, MySQL, MongoDB
• Version control (Git); Linux/Unix
• Preferred: Airflow or Prefect, Docker, Kubernetes, Terraform, SQL, CI/CD tools, data governance and security, GDPR/HIPAA awareness