Staff Data Engineer - Energy Data & Validation Pipelines

KODE Labs; Detroit (MI); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Bonus program

Career development

Flexible PTO

Onboarding program

Friendly environment

Social events

Job summary

KODE Labs in Detroit, MI is seeking a Staff Data Engineer - Energy Data to build end-to-end data pipelines that transform raw energy and meter data into trusted datasets for calculations.

You'll design validation rules, implement cleaning and normalization, and collaborate with Energy, Integrations, Digital Twin and Data teams to productize validation tooling and scalable pipelines for multiple meters and buildings.

Qualifications

• Strong data engineering experience with IoT, meter, or high‑volume time‑series data.
• Strong SQL and Python skills with production-grade systems experience.
• Experience building data validation, cleaning, anomaly detection, and data‑quality pipelines.
• Understanding of time‑series challenges like gaps, duplicates, and stale data.
• Knowledge of energy concepts such as consumption, demand, meters, cost, and unit normalization.
• Experience building scalable data pipelines and modern data processing/storage tech.
• Strong problem‑solving and ability to translate data‑quality scenarios into reusable solutions.
• Ability to collaborate across data, software, product, and domain teams.

Responsibilities

• Define and implement energy meter validation rules across integrations, meter types, units, and building configurations.
• Build production-grade validation, cleaning, and normalization pipelines transforming raw meter data into trusted datasets.
• Validate incoming integration data for completeness, freshness, schema consistency, timestamps, and units.
• Use Digital Twin context to validate meter identity, units, hierarchy, and reporting frequency.
• Develop detection and handling logic for spikes, outliers, gaps, duplicates, and missing data.
• Build robust logic for cumulative-to-interval conversion including resets, rollovers, and negative deltas.
• Establish quality flags, confidence indicators, and lineage between raw, cleaned, and corrected values.
• Develop reusable validation patterns scalable across customers, buildings, and meter types.
• Build monitoring and observability around energy data quality to catch issues early.
• Partner with Energy, Integrations, Digital Twin, and Data teams to align upstream/downstream needs.
• Work with engineers to productize validation logic into reusable tooling, APIs, and workflows.
• Continuously improve validation and cleaning as new integrations and data scenarios emerge.

Skills

IoT data

SQL

Python

Data validation

Time-series data

Energy concepts

Data pipelines

Collaboration

Anomaly detection

Cleaning

Job description

KODE Labs in Detroit, MI is seeking a Staff Data Engineer - Energy Data to build end-to-end data pipelines that transform raw energy and meter data into trusted datasets for calculations.

You'll design validation rules, implement cleaning and normalization, and collaborate with Energy, Integrations, Digital Twin and Data teams to productize validation tooling and scalable pipelines for multiple meters and buildings.