The Company

We are excited to partner with Gridware, a fast-growing grid-resiliency company in San Francisco. They exist to enhance and protect the mother of all networks: the electrical grid. The grid touches everything grinds to a halt, and the consequences can be dire: wildfires burn, land is destroyed, property is damaged, progress stops, and lives are lost.  

Their team of engineers has built an advanced sensing system to continuously analyze both the electrical and mechanical behavior of grid assets. Utilizing high precision sensor arrays, the system identifies and allows preemptive mitigation of faults. The technology has been proven with utilities to bolster safety, reliability, and reduce customer outage durations. The demand for power will only increase. They protect the grid of today while we build the grid of tomorrow.

Gridware is privately held and backed by the best climate-tech and Silicon Valley investors. They are headquartered in the Bay Area in northern California.

Your Impact (Responsibilities)

The Senior Data Engineer is responsible for designing, building, and optimizing data pipelines and infrastructure to support real-time grid monitoring systems. This role involves handling large-scale sensor data, ensuring data integrity, and enabling seamless data flow for analysis and decision-making.

• Design, develop, and maintain scalable data pipelines and architectures.
• Implement data ingestion, transformation, and storage solutions.
• Ensure data quality and integrity across various data sources and destinations.
• Collaborate with software engineers, data scientists, analysts, and other stakeholders to meet data requirements.
• Optimize and tune data workflows for performance and efficiency.
• Monitor, troubleshoot, and resolve issues in data pipelines and related systems.
• Document data processes, architecture, and workflow procedures.

About You

• 5+ years’ proven experience in data engineering or a similar role.
• Strong proficiency in SQL and experience with relational and time series databases
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka).
• Proficiency in Python
• Experience with Databricks, Grafana
• Knowledge of data modeling, ETL processes, and data warehousing concepts.
• Knowledge of version control, automated deployments, and testing pipelines
• Familiarity with data governance and data security best practices.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.