We are looking for a highly skilled and experienced Senior Data Engineer with strong expertise in Google Cloud Platform (GCP) to design, build, and optimize scalable, secure, and high-performance data pipelines and cloud-native data architectures.
The ideal candidate should possess deep hands-on experience in large-scale data engineering, ETL/ELT pipeline development, real-time data processing, and cloud-based data warehousing solutions. This role is best suited for a self-driven professional who can independently manage complex data projects in a remote / freelance work environment.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines and workflows on GCP
• Build robust data architectures using BigQuery, Dataflow, Cloud Storage, and Cloud Composer
• Develop and optimize ETL/ELT pipelines for structured and unstructured data from multiple data sources
• Implement real-time and batch data processing solutions
• Ensure data quality, integrity, governance, security, and compliance
• Optimize performance, scalability, and cost efficiency of GCP-based solutions
• Design and maintain data warehouse schemas, data models, and partitioning strategies
• Work closely with data scientists, BI teams, analysts, and engineering stakeholders
• Implement monitoring, alerting, and troubleshooting mechanisms for data pipelines
• Resolve complex data engineering and performance bottlenecks
• Follow best practices for data lifecycle management, backup, and disaster recovery
• Support CI/CD deployment processes for data engineering workflows
Required Skills & Qualifications:
• 10 - 15 years of experience in Data Engineering / Data Platform roles
• Strong hands-on expertise in Google Cloud Platform (GCP)
• Proven experience in:
• BigQuery
• Dataflow (Apache Beam)
• Cloud Composer (Airflow)
• Cloud Storage
• Pub/Sub
• Strong proficiency in Python and SQL
• Experience with distributed data processing frameworks
• Expertise in data warehousing, data modeling, schema design
• Strong experience in ETL/ELT architecture and pipeline optimization
• Familiarity with streaming platforms such as Kafka / Pub/Sub
• Experience with Git, CI/CD pipelines, and deployment automation
• Strong analytical, debugging, and problem-solving skills
• Ability to work independently in a remote and outcome-driven setup
Preferred Qualifications:
• GCP Professional Data Engineer Certification
• Experience with Docker and Kubernetes
• Exposure to multi-cloud environments (AWS / Azure)
• Experience in large-scale real-time streaming systems
• Knowledge of Spark, Dataproc, or similar big data ecosystems