As a Lead Data Engineer, you will architect data platforms, manage ETL processes, and ensure data integrity for high-performance analytics, collaborating with cross-functional teams.
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 mission-critical 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 execution-oriented: 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 climate-focused 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 real-time, actionable intelligence.
We partner closely with the Edge Hardware team, which streams high-fidelity, sub-second energy data from our IoT sensors to the cloud. Our team is responsible for modeling, storing, and serving that data to support real-time applications, machine learning, and customer-facing analytics.
We’re currently evolving our core architecture to embrace a modern, scalable data stack, including stream and OLAP-integrated databases like ClickHouse or StarTree (under evaluation), and are laying the foundation for a data mesh architecture. This will enable decentralized, domain-oriented 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 two-week sprint cadence. We primarily work from 10:00am PST to 6:00pm PST. We’re committed to cross-functional collaboration and high-impact 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 cost-effective 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 ETL/ELT 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 real-time 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 AI/ML teams to support model training and inference pipelines.
- Work with web and application teams to ensure real-time 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 large-scale, high-throughput systems
- Proven experience designing dimensional models and OLAP schema (fact/dimension 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 updates/inserts/type-2 dimensions for time-series or large-scale event stores
Preferred Qualifications
- Experience with BMS/HVAC 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 mission-driven startup. We’re innovating for the energy management industry hoping to positively affect climate change. Verdigrisians aim to be ego-free authorities in our fields. We take our work seriously and strive for an opportunity-filled 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.
Top Skills
Airflow
AWS
Clickhouse
Dagster
Flink
Kafka
Postgres
Python
Spark Streaming
SQL
Startree
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