About the Role
Design and implement robust backend services to manage high-volume energy-related time series data and streamline data flow architectures across distributed systems.
Responsibilities
- Develop and maintain backend services handling large-scale energy datasets
- Optimize ingestion and processing of time series data streams
- Design reliable data pipelines for real-time and batch processing
- Ensure data consistency and integrity across storage systems
- Collaborate with data engineers to refine data models
- Write clean, testable, and well-documented code
- Troubleshoot production issues in distributed environments
- Support integration of forecasting and analytics modules
- Implement monitoring for data flow health and performance
- Work closely with frontend teams to expose data via APIs
- Contribute to architectural decisions for scalability
- Maintain security standards in data handling
- Participate in code reviews and technical planning
- Improve system reliability and fault tolerance
- Optimize database queries for time series workloads
- Evaluate and integrate new data technologies
- Ensure compliance with data governance policies
- Support deployment automation and CI/CD pipelines
- Document system design and data workflows
- Assist in capacity planning for data growth
- Collaborate on incident response and post-mortems
- Refactor legacy components for better maintainability
- Integrate third-party energy data sources
- Enhance logging and observability across services
- Contribute to disaster recovery planning
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible hours
Team
Collaborative team focused on energy data systems
Why This Role Matters
Energy systems generate vast amounts of time-stamped data that require specialized handling. This role directly impacts how efficiently data is collected, stored, and made available for analysis and decision-making across the organization.
Technology Stack
- Primary languages: Python, SQL
- Databases: PostgreSQL, TimescaleDB, InfluxDB
- Infrastructure: AWS, Docker, Kubernetes, Terraform
- Data tools: Kafka, Prometheus, Grafana, Airflow
Growth Opportunities
- Opportunities to lead technical initiatives
- Mentorship in data architecture and systems design
- Exposure to energy sector challenges and innovations
Available for qualified candidates
