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Gridware

Posted 7 months ago

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Senior Data Engineer, Data Lake & Governance

San FranciscoOn-siteFull-time

AI Summary

Senior Data Engineer designs and scales data infrastructure for real-time grid monitoring, building high-performance pipelines to transform sensor streams into actionable insights and ensure data quality and governance.

About this role

About Gridware
Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

Role Description
As a Senior Data Engineer at Gridware, you’ll design and scale the data infrastructure that powers our real-time grid monitoring platform. You’ll build high-performance pipelines that transform massive streams of sensor and telemetry data into actionable insights - helping detect faults, predict failures, and strengthen the grid that powers entire communities.

Responsibilities

  • Deploy and manage Unity Catalog to standardize data governance, lineage, and access control across data domains.
  • 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 of professional experience in data engineering or related roles, building and scaling real-time data infrastructure
  • Experience designing and maintaining data lakes and lakehouse architectures with governance and access controls
  • Strong in Python and SQL, with deep experience in relational, time-series, and streaming databases
  • Hands-on with modern data stacks - Spark, Kafka, Databricks, Grafana, and other cloud-native tools
  • Skilled in data modeling, ETL/ELT pipelines, and real-time streaming architectures for production systems
  • Familiar with CI/CD, version control, and data governance/security best practices

    • Bonus Skills

  • Experience with real-time data processing and streaming analytics frameworks
  • Familiarity with IoT and embedded systems, including sensor data pipelines and edge computing
  • Hands-on with Docker, Kubernetes, and Protobuf in production environments
  • Exposure to machine learning workflows and real-time monitoring for IoT and time-series data
  • Comfortable operating in a high-growth startup environment, adapting quickly across domains

    • Skills

    CI/CDCloud-native ToolsDataDatabricksData Governance/securityData IngestionData LakesData LineageData ModelingData PipelinesData QualityData StorageDockerEdge ComputingETL/ELTGovernanceGrafanaIoTKafkaKubernetesLakehouseProtobufPrototypingPythonReal-time StreamingSparkSQLStreaming DatabasesTime-series DatabasesUnity CatalogVersion Control

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