Offer summary

Qualifications:

At least 5 years of experience in data engineering with large-scale systems., Proficiency in SQL and Python for data pipelines., Experience designing dimensional models and OLAP schemas., Deep understanding of columnar stores and database internals like ClickHouse or StarTree..

Key responsibilities:

Design and maintain scalable data storage solutions.

Lead data architecture decisions and evaluate tools in the data stack.

Build and manage ETL/ELT pipelines for data ingestion and transformation.

Collaborate with teams to support real-time analytics and data governance.

Job description

Mission, Vision, Values

Verdigris is on a mission to sustain and enrich human life through responsive energy intelligence. Our AI sensors automate energy management and predict unseen equipment failures in missioncritical buildings. This is a critical step for autonomous, sustainable environments responsive to their inhabitants.

About You

You are deeply interested in how data flows — not just pipelines and tooling, but also how data is modeled, validated, and used to make decisions. You care about the structure and quality of data, and you take pride in designing systems that are reliable, scalable, and performant.

You’re executionoriented: you like to ship, iterate, and improve. You’re comfortable navigating ambiguity and thrive in environments where the architecture is evolving. You enjoy tracking down data anomalies, validating assumptions, and making the invisible visible. You take ownership of your work, ask thoughtful questions, and collaborate well across disciplines.

You’re motivated by purpose building something that has impact, not just technically, but in the real world. You’re excited by the opportunity to shape the foundations of a modern data platform that supports climatefocused outcomes at scale.

About the Team

At Verdigris, our cloud software (data, web, ML) are a single team, collaborating to deliver insights that help data centers and other critical facilities optimize energy use and reduce carbon impact. We design and maintain APIs and data products that transform raw sensor data into realtime, actionable intelligence.

We partner closely with the Edge Hardware team, which streams highfidelity, subsecond energy data from our IoT sensors to the cloud. Our team is responsible for modeling, storing, and serving that data to support realtime applications, machine learning, and customerfacing analytics.

We’re currently evolving our core architecture to embrace a modern, scalable data stack, including stream and OLAPintegrated databases like ClickHouse or StarTree (under evaluation), and are laying the foundation for a data mesh architecture. This will enable decentralized, domainoriented data ownership and empower us to move faster with more reliable, discoverable, and performant data. You will help us design and implement this data architecture and migrate existing data.

We operate as a fully remote team with daily virtual standups and a twoweek sprint cadence. We primarily work from 10:00am PST to 6:00pm PST. We’re committed to crossfunctional collaboration and highimpact delivery.

Core Responsibilities
Collaborate with Product Management, Understand use cases and personas, and engineer product to support a strong user experience.
Own schema design and data modeling for energy metering and building management system (BMS) data.
Architect and maintain costeffective and performant next generation data storage (e.g. ClickHouse, StarTree, etc).
Lead data architecture decisions, including evaluating and integrating tools in our modern data stack.
Build and manage robust, scalable ETLELT pipelines to ingest, transform, and serve data
Ensure performance and efficiency of analytical queries across large datasets
Develop and enforce data quality, validation, and governance standards

Adjacent Responsibilities
Support realtime IoT analytics and streaming pipelines.
Owning BI tooling (e.g. Superset, Looker, Tableau, etc).
Contribute to building internal data tools for engineers and analysts.
Collaborate with AIML teams to support model training and inference pipelines.
Work with web and application teams to ensure realtime and batch data access needs are met.
Manage team projects and coordinate with other technical leads.
Mentor junior engineers and contribute to technical hiring.

Required Qualifications
Align with core working hours, 10:00AM PST to 5:00PM PST in either pacific, mountain, or central timezones.
5+ years of experience in data engineering with largescale, highthroughput systems
Proven experience designing dimensional models and OLAP schema (factdimension tables)
Deep understanding of columnar stores and database internals (e.g., ClickHouse, Druid, StarTree, Pinot)
Strong SQL skills and proficiency with Python for data pipelines
Experience handling updatesinsertstype2 dimensions for timeseries or largescale event stores

Preferred Qualifications
Experience with BMSHVAC or Energy data is a plus
Experience with usage of time series and energy data used for diagnostics and efficiency.
Experience with IoT or sensor data systems.
Experience working in AWS Cloud.
Experience with Postgres.
Proficiency in orchestrating ETL workflows (e.g. Dagster, Airflow, AWS Step Functions, etc.)
Familiarity with stream processing tools (e.g., Kafka, Flink, Spark Streaming)
Exposure to machine learning feature stores or MLOps tooling
Experience with data observability and data cataloging tools
Experience managing a team or others.
Applying to Verdigris is a chance to make an impact by joining a missiondriven startup. We’re innovating for the energy management industry hoping to positively affect climate change. Verdigrisians aim to be egofree authorities in our fields. We take our work seriously and strive for an opportunityfilled environment supportive of curious minds.

You can expect thoughtful, hardworking, and funny teammates. We value differing perspectives and embrace candid, direct and constant feedback. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, origin, gender, orientation, age, or status.