Data Engineer (GCP & AI/ML)

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Job Summary:

We are seeking an experienced Data Engineer hands-on experience in designing, building, and managing large-scale data pipelines and cloud-based data infrastructure. The ideal candidate will have strong expertise in Google Cloud Platform (GCP) and experience integrating data from web and mobile applications, including React-based systems and Firebase services. You will play a key role in ensuring the reliability, scalability, and efficiency of data pipelines while collaborating closely with developers, data scientists, and product teams to deliver high-quality, actionable data solutions.

Key Responsibilities:

1. Data Pipeline Development:

• Design, build, and maintain scalable and efficient data pipelines to ingest, process, and transform large datasets from web and mobile applications.
• Implement ETL (Extract, Transform, Load) processes to integrate data from multiple sources, including Firebase (Firestore, Firebase Analytics).
• Optimize data workflows for performance, reliability, and cost-efficiency in cloud environments.

2. Data Infrastructure Management:

• Develop and manage data storage solutions (databases, data warehouses, data lakes) to support back-end and analytical needs.
• Configure and maintain cloud-based data infrastructure, ensuring scalability, security, and high availability.
• Automate infrastructure tasks such as schema migrations, data partitioning, and backup management for seamless operations.

3. Data Integration & API Development:

• Build and maintain APIs and data access layers to enable seamless data integration with React-based and cloud-native applications.
• Consolidate and unify data from disparate sources for analytics and product functionalities.
• Ensure data consistency, integrity, and synchronization across systems, supporting both batch and real-time data processing.

4. Collaboration & Communication

• Partner with data scientists, software developers, and product managers to understand data requirements and deliver effective data solutions.
• Provide regular updates on data infrastructure health, data availability, and pipeline performance.
• Collaborate with engineering teams to integrate pipelines with production environments, including Firebase-hosted systems.

5. Data Quality & Monitoring

• Implement robust data quality checks and validation mechanisms.
• Monitor and troubleshoot pipeline performance and data latency using cloud monitoring tools.
• Maintain documentation, metadata, and data lineage for compliance and traceability.

Required Skills:

• Minimum 4 years of professional experience in Data Engineering.
• Hands-on experience with at least one public cloud platform — Google Cloud Platform (preferred), AWS, or Azure.
• Strong knowledge of ETL development, SQL/NoSQL databases, data modeling, and pipeline orchestration.
• Experience with Firebase, Firestore, and React-based data integrations is a strong plus.
• Proficiency in Python, SQL, and cloud-native data tools (e.g., Dataflow, BigQuery, Airflow).
• Familiarity with CI/CD, API development, and infrastructure automation.

Preferred Qualifications:

• GCP certification (Data Engineer or Architect).
• Experience with real-time data streaming (e.g., Pub/Sub, Kafka).
• Strong analytical and problem-solving skills with a focus on performance optimization.