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.
