Voltus

Voltus

Voltus is a leading company that helps commercial and industrial customers maximize their energy revenue through demand response programs. By leveraging their award-winning technology, Voltus pays users to reduce electricity consumption, creates new re...

Electric Utilities
251-1K
Founded 2016
$66M raised

Description

  • Own and maintain data pipeline architectures, including ingestion services, ETL pipelines, database mirroring, and warehousing.
  • Ensure data systems are reliable, monitored, and meeting service-level agreements.
  • Manage and evolve the data modeling environment and support a documented workflow for analysts and engineers.
  • Operate and improve orchestration systems such as Dagster so jobs run reliably and are observable.
  • Evaluate and rationalize data tooling across notebooks, Databricks, and BI/analytics platforms to support a sustainable data platform.
  • Implement logging, alerting, and metrics for data system observability and continuous data quality monitoring.
  • Champion data governance and documentation so datasets are well-defined, trustworthy, and easy to navigate.
  • Collaborate with analysts, data scientists, and platform engineers to deliver intuitive, scalable infrastructure.
  • Make data reliably accessible through well-documented interfaces to support future machine learning and AI use cases.
  • Serve as the point person for reliability and technical direction on critical data infrastructure.

Requirements

  • Proven experience in a data engineering or infrastructure role with production-grade pipelines and data systems.
  • Strong programming ability in Python; Go is a bonus.
  • Deep experience with ETL/ELT pipelines, dbt, and integrating disparate data sources into warehouses or lakes.
  • Experience with cloud data platforms, especially AWS; familiarity with GCP is also valued.
  • Hands-on experience with workflow orchestration tools such as Airflow, Dagster, or similar.
  • Ability to evaluate tradeoffs across notebook and analysis platforms such as Jupyter, Marimo, and Databricks.
  • Knowledge of BI/analytics tools such as Redash, Looker, Mode, or Superset, including support or migration considerations.
  • Strong understanding of data quality, governance, and observability.
  • Clear communication skills for working across technical and non-technical teams.
  • Comfort taking end-to-end ownership of critical data infrastructure.
  • Familiarity with observability and monitoring tools such as Datadog or Prometheus.
  • Experience with Delta Lake, Databricks, or DuckDB is a bonus.
  • Exposure to LLM-based applications and toolchains such as LangChain, LlamaIndex, or lite-llm is a bonus.
  • Experience with vector databases such as Pinecone, Qdrant, or Chroma is a bonus.
  • Must include a GitHub link in the application.
  • Must be authorized to work from a home location in the US or Canada, unless otherwise indicated.
  • Cannot require visa sponsorship or transfer for new hires.

Benefits

  • Base salary of $160,000 to $190,000 per year, depending on experience.
  • 10% bonus paid semi-annually.
  • Equity compensation.
  • Unlimited leave for full-time employees.
  • Parental leave.
  • Comprehensive benefits package.
  • Remote-first work environment.
  • Opportunity to work on business-critical production data systems at a fast-growing climate-tech company.

Interested in this position?

Apply directly on the company website

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