Data Engineer - Energy Data
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- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDefine and implement energy meter validation rules across integrations, meter types, units, reporting frequencies, and building configurations.
Build production-grade validation, cleaning, and normalization pipelines that transform raw meter data into trusted, calculation-ready datasets.
Develop detection and handling logic for spikes, outliers, gaps, duplicates, stale values, and missing data.
From the employer’s posting
What You Will Do Define and implement energy meter validation rules across integrations, meter types, units, reporting frequencies, and building configurations. Build production-grade validation, cleaning, and normalization pipelines that transform raw meter data into trusted, calculation-ready datasets.
Define and implement energy meter validation rules across integrations, meter types, units, reporting frequencies, and building configurations. Build production-grade validation, cleaning, and normalization pipelines that transform raw meter data into trusted, calculation-ready datasets. Validate incoming integration data for completeness, freshness, schema consistency, timestamps, units, and expected behavior.
Use Digital Twin context to validate meter identity, units, hierarchy, equipment relationships, and expected reporting frequency. Develop detection and handling logic for spikes, outliers, gaps, duplicates, stale values, and missing data. Build robust logic for cumulative-to-interval conversion, including meter resets, rollovers, replacements, negative deltas, and invalid drops.
What you’ll bring
All qualificationsCore experience
- Strong SQL and Python skills, with the software engineering experience to build reliable production systems.
- Experience building data validation, cleaning, anomaly detection, and data-quality pipelines.
- Strong understanding of time-series data challenges, including gaps, irregular intervals, duplicates, timestamps, stale data, and outliers.
- Understanding of energy concepts such as consumption, demand, cumulative and interval meters, cost, EUI, and unit normalization.
- Experience building scalable data pipelines and working with modern data processing and storage technologies.
- Ability to collaborate effectively across data, software engineering, product, and domain teams.
Qualification wording
Strong SQL and Python skills, with the software engineering experience to build reliable production systems.
Experience building data validation, cleaning, anomaly detection, and data-quality pipelines.
Strong understanding of time-series data challenges, including gaps, irregular intervals, duplicates, timestamps, stale data, and outliers.
Understanding of energy concepts such as consumption, demand, cumulative and interval meters, cost, EUI, and unit normalization.
Experience building scalable data pipelines and working with modern data processing and storage technologies.
Ability to collaborate effectively across data, software engineering, product, and domain teams.
Tools in this posting
- Python
- SQL
Source — Tool mentions in context
- Strong data engineering experience working with IoT, meter, operational, or high-volume time-series data. - Strong SQL and Python skills, with the software engineering experience to build reliable production systems. - Experience building data validation, cleaning, anomaly detection, and data-quality pipelines.
Benefits in the posting
Full benefits wording- Competitive salary based on experience
- Discretionary Bonus Program
- Career Development Program and opportunities to grow within the company
- Flexible Paid Time Off
- Comprehensive Health Insurance Package
- Dynamic team and challenging projects
- Custom-tailored onboarding experience
- Welcoming and friendly work environment
- Social events and team activities
- JOIN THE TEAM
- KODE Labs is a real estate technology company founded in 2017 with a mission to change the way people, buildings, and systems operate. Headquartered in Detroit, Michigan, we are a driving force behind the adoption of smart building technology. To scale our presence across numerous cities and countries, we depend on our team of talented, ambitious people who go above and beyond to create value for our clients.
- If KODE Labs sounds like the place for you, we’d love to hear your story, so please apply through our online application form. Only shortlisted candidates will be contacted.
From the employer’s posting.
Posting record
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- Live
- First seen by us
- Aug 23, 2026 · 54d ago
- Recorded sightings
- 80
- Last seen by us
- Oct 15, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Our team at KODE Labs is looking for a Data Engineer — Energy Data to build the systems that turn raw energy and meter data into trusted, calculation-ready datasets.
In this role, you’ll combine strong data and software engineering skills with an understanding of time-series and energy data. You’ll define validation and cleaning logic, build production-grade pipelines, and partner with software engineers to turn these capabilities into scalable, reusable parts of KODE OS.
What You Will Do
Define and implement energy meter validation rules across integrations, meter types, units, reporting frequencies, and building configurations.
Build production-grade validation, cleaning, and normalization pipelines that transform raw meter data into trusted, calculation-ready datasets.
Validate incoming integration data for completeness, freshness, schema consistency, timestamps, units, and expected behavior.
Use Digital Twin context to validate meter identity, units, hierarchy, equipment relationships, and expected reporting frequency.
Develop detection and handling logic for spikes, outliers, gaps, duplicates, stale values, and missing data.
Build robust logic for cumulative-to-interval conversion, including meter resets, rollovers, replacements, negative deltas, and invalid drops.
Establish quality flags, confidence indicators, and clear lineage between raw, cleaned, and corrected values.
Develop reusable validation patterns that can scale across customers, buildings, integrations, and different types of meters.
Build monitoring and observability around energy data quality so issues can be identified before they impact downstream calculations or customer-facing products.
Partner with Energy, Integrations, Digital Twin, and Data teams to understand upstream data behavior and downstream calculation requirements.
Work closely with software engineers to productize validation logic into reusable tooling, APIs, monitoring workflows, and automated validation systems.
Continuously improve validation and cleaning approaches as new integrations, meter types, and data-quality scenarios emerge.
Requirements
Requirements
Strong data engineering experience working with IoT, meter, operational, or high-volume time-series data.
Strong SQL and Python skills, with the software engineering experience to build reliable production systems.
Experience building data validation, cleaning, anomaly detection, and data-quality pipelines.
Strong understanding of time-series data challenges, including gaps, irregular intervals, duplicates, timestamps, stale data, and outliers.
Understanding of energy concepts such as consumption, demand, cumulative and interval meters, cost, EUI, and unit normalization.
Experience building scalable data pipelines and working with modern data processing and storage technologies.
Strong problem-solving skills and the ability to translate complex data-quality scenarios into reusable engineering solutions.
Ability to collaborate effectively across data, software engineering, product, and domain teams.
Benefits
Competitive salary based on experience
Discretionary Bonus Program
Career Development Program and opportunities to grow within the company
Flexible Paid Time Off
Comprehensive Health Insurance Package
Dynamic team and challenging projects
Custom-tailored onboarding experience
Welcoming and friendly work environment
Social events and team activities
JOIN THE TEAM
KODE Labs is a real estate technology company founded in 2017 with a mission to change the way people, buildings, and systems operate. Headquartered in Detroit, Michigan, we are a driving force behind the adoption of smart building technology. To scale our presence across numerous cities and countries, we depend on our team of talented, ambitious people who go above and beyond to create value for our clients.
When you join the KODE Labs team you can create your own career. Whether you have years of experience or are just starting, we help you realize your full potential and achieve your goals.
If KODE Labs sounds like the place for you, we’d love to hear your story, so please apply through our online application form. Only shortlisted candidates will be contacted.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on kodelabs.zohorecruit.com. The employer’s form will show what is required.
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