{"id":2305978,"url":"https://alion.io/job/kode-labs-data-engineer-energy-data","title":"Data Engineer - Energy Data","company":{"id":4414432,"name":"Kode Labs","domain":"kodelabs.com","url":"https://alion.io/company/kode-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Digital Twin","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-10-11T22:54:17Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-13T04:48:32Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"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.\nIn 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.\nWhat You Will Do\nDefine and implement energy meter validation rules across integrations, meter types, units, reporting frequencies, and building configurations.\n\nBuild production-grade validation, cleaning, and normalization pipelines that transform raw meter data into trusted, calculation-ready datasets.\n\nValidate incoming integration data for completeness, freshness, schema consistency, timestamps, units, and expected behavior.\n\nUse Digital Twin context to validate meter identity, units, hierarchy, equipment relationships, and expected reporting frequency.\n\nDevelop detection and handling logic for spikes, outliers, gaps, duplicates, stale values, and missing data.\n\nBuild robust logic for cumulative-to-interval conversion, including meter resets, rollovers, replacements, negative deltas, and invalid drops.\n\nEstablish quality flags, confidence indicators, and clear lineage between raw, cleaned, and corrected values.\n\nDevelop reusable validation patterns that can scale across customers, buildings, integrations, and different types of meters.\n\nBuild monitoring and observability around energy data quality so issues can be identified before they impact downstream calculations or customer-facing products.\n\nPartner with Energy, Integrations, Digital Twin, and Data teams to understand upstream data behavior and downstream calculation requirements.\n\nWork closely with software engineers to productize validation logic into reusable tooling, APIs, monitoring workflows, and automated validation systems.\n\nContinuously improve validation and cleaning approaches as new integrations, meter types, and data-quality scenarios emerge.\n\nRequirements\nRequirements\nStrong data engineering experience working with IoT, meter, operational, or high-volume time-series data.\n\nStrong SQL and Python skills, with the software engineering experience to build reliable production systems.\n\nExperience building data validation, cleaning, anomaly detection, and data-quality pipelines.\n\nStrong understanding of time-series data challenges, including gaps, irregular intervals, duplicates, timestamps, stale data, and outliers.\n\nUnderstanding of energy concepts such as consumption, demand, cumulative and interval meters, cost, EUI, and unit normalization.\n\nExperience building scalable data pipelines and working with modern data processing and storage technologies.\n\nStrong problem-solving skills and the ability to translate complex data-quality scenarios into reusable engineering solutions.\n\nAbility to collaborate effectively across data, software engineering, product, and domain teams.\n\nBenefits\nCompetitive salary based on experience \n\nDiscretionary Bonus Program \n\nCareer Development Program and opportunities to grow within the company \n\nFlexible Paid Time Off\n\nComprehensive Health Insurance Package \n\nDynamic team and challenging projects \n\nCustom-tailored onboarding experience \n\nWelcoming and friendly work environment \n\nSocial events and team activities\n\nJOIN THE TEAM\nKODE 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.\nWhen 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.\nIf KODE Labs sounds like the place for you, we’d love to hear your story, so please apply through our online application form. 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