Senior Data Engineer

Number of employees

85

San Francisco, CA, United States

Posted on: 2025-02-10

Category: energy

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Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

Gridware exists to enhance and protect the mother of all networks: the electrical grid. The grid touches everyone and makes our modern economy possible. But it’s also fragile. When the grid is compromised, 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.  

Our team builds smart sensors that help utility companies to immediately detect, find, and fix outages and take steps to prevent new outages, and other related disasters, from happening at all. The need for power will only increase. We 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. We are headquartered in the Bay Area in northern California. 

About Gridware
Gridware exists to enhance and protect the mother of all networks: the electrical grid. The grid touches everything and the consequences can be dire when it fails: wildfires burn, land is destroyed, property is damaged, and lives are lost.

Our team created an advanced sensing system to continuously analyze critical grid behavior. Utilizing high-precision sensor arrays and intelligence, our system identifies and preemptively mitigates faults. The technology has been proven with utilities to bolster safety, enhance reliability, and reduce outages. The demand for power will only increase. We 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. We are headquartered in San Francisco, California.

Role Description
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.

This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!

Benefits
Health, Dental & Vision (Gold and Platinum with some providers plans fully covered) 
Paid parental leave 
Alternating day off (every other Monday)
“Off the Grid”, a two week per year paid break for all employees. 
Commuter allowance 
Company-paid training 

Responsibilities

  •  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.
  • Required Skills

  • 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.
  • Bonus Skills

  • Knowledge of machine learning and data science concepts.
  • Experience with real-time data processing frameworks
  • Familiarity with IOT / embedded systems
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Experience in high-growth startup environments where you must wear many hats
  • Experience with Protobuf
  • Familiarity with monitoring and alerting systems for real-time IoT time series analysis.
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