Laravel
Laravel
Staff Data Engineer On-site – Electricity Maps , Copenhagen
Bliv en del af Electricity Maps som staff data engineer. Bidrag med On-site, Full-time, Machine Learning og nyd anpartsselskab.
Jobinformation
Titel

Staff Data Engineer

Lokation

Copenhagen, Capital Region of Denmark, Denmark

Opslået Dato

Sep 29, 2025

Påkrævede Færdigheder
Full Time
Programmeringssprog
HTML
JavaScript
Python
3 sprog
Databaser & Datalagring
PostgreSQL
BigQuery
2 databaser
Udviklingsværktøjer & Infrastruktur
GCP
1 værktøjer
Færdigheder & Teknologier
Fysisk tilstedeværelse
Machine learning
Training
Google cloud platform (gcp)
Forecasting
Engineering
Scalability
Programming
Back-end web development
9 færdigheder
Total: 16 krav listet (3 sprog, 0 frameworks, 2 databaser, 1 værktøjer, 9 andre færdigheder)
Virksomhedsinformation
Electricity Maps logo
Electricity Maps

IT-infrastruktur, databehandling, hosting og relaterede aktiviteter

CVR-nummer: 39101211
Medarbejdere: 31
Status:
Normal
Branche: IT-infrastruktur, databehandling, hosting og relaterede aktiviteter
Type:
APS
Anpartsselskab
Grundlagt: November 4, 2022
Beskyttet:
Ja
Adresse:
Bragesgade 8
2200 København N
Jobvurdering
Job Ikke Vurderet Endnu

Dette job er ikke blevet analyseret af vores AI-vurderingssystem. Klik på knappen nedenfor for at få en AI-drevet match score baseret på dine præferencer.

Kompetenceudvikling
Kompetenceudvikling
Completed
100% Confidence
Uddragne Færdigheder (4)
Python
Nævnt som: Python
Our stack: Python, PostgreSQL, BigQuery, and GCP.
languages
100%
PostgreSQL
Nævnt som: PostgreSQL
Our stack: Python, PostgreSQL, BigQuery, and GCP.
databases
100%
BigQuery
Nævnt som: BigQuery
Our stack: Python, PostgreSQL, BigQuery, and GCP.
databases
100%
GCP
Nævnt som: GCP, Google Cloud Platform
Our stack: Python, PostgreSQL, BigQuery, and GCP.
tools
100%
Analyse Detaljer
Totale Færdigheder Fundet: 4
Færdigheder efter Kategori:
languages: 1 færdigheder
frameworks: 0 færdigheder
databases: 2 færdigheder
tools: 1 færdigheder
Forbedret den: October 6, 2025 at 11:15 AM Omkostning: $0.0061
🔍 Debug Information (Klik for at udvide)
Fuld AI Prompt:
# Job Skill Enhancement System

## CORE INSTRUCTION:
You are an AI that extracts and identifies coding languages and frameworks from job descriptions. Your goal is to find ALL relevant technical skills mentioned in the job posting, even if they're mentioned in different ways or aliases.

## INPUT DATA:
{
  "job": {"job_id":4449,"title":"Staff Data Engineer","company_name":"Electricity Maps","description":"About the job\n\nWe’ve built a system that predicts various signals about the electricity system on a 72 hour horizon, worldwide. Now we’re in the process of expanding the dimensions, horizons, and granularity of our forecasts. We’re building a platform that can generate high-quality forecasts without requiring bespoke engineering effort for each signal or geographical area.\n\nTo help us move quickly, we’re looking for an experienced data engineer to join our team. Our ideal candidate has scaled ML systems and designed pipelines for large-scale time series data, supporting all stages of the model life cycle while keeping complexity low.\n\nWe’re looking for an experienced Data Engineer who thrives on tackling complex scaling challenges, enjoys collaborating and isn’t afraid to get hands-on with implementation.\n\nAbout Electricity Maps 🌎\n\nElectricity Maps is on a mission to accelerate the transition to a decarbonized electricity system. Our platform provides real-time and forecasted electricity data, helping companies like Google and Cisco to unlock flexibility and reduce emissions.\n\n\nOur free map product is used by millions of people around the world\nOur API powers products at some of the world’s largest enterprises\nWe’re backed by top-tier investors with deep experience scaling developer-first, climate-focused companies\n\n\nWhat You’ll Build and Own 🧱\n\nYou’ll work on data pipelines, feature stores, and ML infrastructure that is flexible enough to predict multiple signals in over 350 regions around the world.\n\nToday, Our Signals Are\n\n\nLoad\nDay-ahead prices\nCarbon intensity\nRenewable energy %\nElectricity mix (all generation sources) \n\n\nWe have the vision to keep adding more signals and features to our forecasting platform such as: balancing prices and curtailment.\n\nYou’ll\n\n\nShape and build solutions with our lead and other engineers on the team\nShip fast, iterate based on real feedback, and own your work in production\nRefine how we build, deploy, and scale across the stack\n\n\nYou’ll Thrive Here If You… 🔍\n\n\nHave built ML systems at scale (feature stores, model registries, experimentation → training → inference → monitoring)\nHave experience with time series forecasting and handling millions of data points\nBalance pragmatism with ambition: scoping to fit the appetite, not over-engineering\nEnjoy fast-paced, high-impact cycles and making product\/technical decisions independently\nCare about usability, performance, and delivering real value to users\nMentor colleagues, spar with peers, and raise the team’s overall level\nOur stack: Python, PostgreSQL, BigQuery, and GCP. No need for exact matches 🫶🏻 just be comfortable working across modern data platforms.\n\n\nBonus points if you…\n\n\nBring experience from the energy domain\n\n\nRole Details📍\n\n\nFull-time\nBased in Copenhagen\nCompetitive salary + stock options\n6 weeks vacation + full health insurance","brief_summary_of_job":null,"existing_skills_from_job":["On-site","Full-time","Machine Learning","Training","Google Cloud Platform (GCP)","HTML","Forecasting","JavaScript","Engineering","Scalability","Programming","Back-End Web Development","Python","PostgreSQL","BigQuery","GCP"],"existing_skills_from_database":[]},
  "coding_categories": {"languages":["Bash","C","C#","C++","CSS","Clojure","Dart","Elixir","Go","Groovy","Haskell","HTML","Java","JavaScript","Julia","Kotlin","Lua","MATLAB","Objective-C","Perl","PHP","PowerShell","Python","R","Ruby","Rust","Sass","Scala","Swift","TypeScript"],"frameworks":[".NET","Angular","Apache Spark","ASP.NET","Backbone.js","Bootstrap","CodeIgniter","Django","Ember.js","Express","FastAPI","Flask","Flutter","Hadoop","Ionic","jQuery","Laravel","Livewire","Meteor","NestJS","Next.js","Node.js","Nuxt.js","Phoenix","PHPUnit","PyTorch","React","React Native","Ruby on Rails","Spring Boot","Svelte","Symfony","Tailwind CSS","TensorFlow","Vue.js","Xamarin","Alpine.js","Filament","WordPress"],"databases":["MySQL","PostgreSQL","Redis","MongoDB","DynamoDB","MariaDB","NoSQL","Oracle","BigQuery","Elasticsearch","SQL","SQL Server","SQLite","Cassandra","CouchDB","Neo4j","InfluxDB","CockroachDB"],"tools":["Git","GitHub","GitLab","Bitbucket","Docker","Kubernetes","CI\/CD","Jenkins","Kafka","RabbitMQ","Amazon SQS","AMQP","PubSub","REST API","RESTful APIs","GraphQL","AWS","Azure","GCP","Terraform","Ansible","Puppet","Chef","Vagrant","Vault","Consul","Prometheus","Grafana","ELK Stack","Splunk"],"skills":["English","Danish","Communication","Full-stack development","Back-end development","Front-end development","Cloud computing","DevOps","Microsoft Excel","PowerBI","Power Platform","Agile","Scrum","Problem-solving","Team collaboration","Physical presence","Remote work","Hybrid work"],"colors":{"languages":"blue","frameworks":"purple","databases":"orange","tools":"indigo"}},
  "skill_aliases": {"bash":"Bash","c":"C","c plus plus":"C++","C plus plus":"C++","c sharp":"C#","C sharp":"C#","c#":"C#","c++":"C++","clojure":"Clojure","cpp":"C++","dart":"Dart","elixir":"Elixir","go":"Go","golang":"Go","Golang":"Go","groovy":"Groovy","haskell":"Haskell","java":"Java","java script":"JavaScript","Java script":"JavaScript","javascript":"JavaScript","Javascript":"JavaScript","js":"JavaScript","JS":"JavaScript","es5":"JavaScript","ES5":"JavaScript","es6":"JavaScript","ES6":"JavaScript","julia":"Julia","kotlin":"Kotlin","lua":"Lua","matlab":"MATLAB","Matlab":"MATLAB","objective c":"Objective-C","Objective C":"Objective-C","objective-c":"Objective-C","objc":"Objective-C","ObjC":"Objective-C","obj-c":"Objective-C","Obj-C":"Objective-C","perl":"Perl","php":"PHP","Php":"PHP","powershell":"PowerShell","Power Shell":"PowerShell","python":"Python","py":"Python","Py":"Python","phyton":"Python","r":"R","ruby":"Ruby","rust":"Rust","scala":"Scala","swift":"Swift","typescript":"TypeScript","Typescript":"TypeScript","ts":"TypeScript","TS":"TypeScript","mysql":"MySQL","postgresql":"PostgreSQL","postgres":"PostgreSQL","mongodb":"MongoDB","mongo":"MongoDB","redis":"Redis","sqlite":"SQLite","oracle":"Oracle","mssql":"SQL Server","sql server":"SQL Server","dynamodb":"DynamoDB","dynamo db":"DynamoDB","mariadb":"MariaDB","maria db":"MariaDB","nosql":"NoSQL","no sql":"NoSQL","bigquery":"BigQuery","big query":"BigQuery","elasticsearch":"Elasticsearch","elastic search":"Elasticsearch","cassandra":"Cassandra","couchdb":"CouchDB","couch db":"CouchDB","neo4j":"Neo4j","neo 4j":"Neo4j","influxdb":"InfluxDB","influx db":"InfluxDB","cockroachdb":"CockroachDB","cockroach db":"CockroachDB","aws":"AWS","amazon web services":"AWS","azure":"Azure","microsoft azure":"Azure","gcp":"GCP","google cloud platform":"GCP","google cloud":"GCP",".Net":".NET","angular":"Angular","angular js":"Angular","Angular js":"Angular","angularjs":"Angular","AngularJS":"Angular","apache spark":"Apache Spark","asp net":".NET","ASP net":".NET","asp.net":"ASP.NET","ASP.NET":".NET","asp.net core":".NET","ASP.NET Core":".NET","backbone":"Backbone.js","BackboneJS":"Backbone.js","backbone js":"Backbone.js","backbonejs":"Backbone.js","bootstrap":"Bootstrap","Bootstrap framework":"Bootstrap","twitter bootstrap":"Bootstrap","Twitter Bootstrap":"Bootstrap","code igniter":"CodeIgniter","codeigniter":"CodeIgniter","django":"Django","ember":"Ember.js","ember js":"Ember.js","emberjs":"Ember.js","EmberJS":"Ember.js","express":"Express","express.js":"Express","Express.js":"Express","expressjs":"Express","ExpressJS":"Express","fast api":"FastAPI","Fast api":"FastAPI","fastapi":"FastAPI","flask":"Flask","flutter":"Flutter","hadoop":"Hadoop","Hadoop":"Hadoop","ionic":"Ionic","Ionic framework":"Ionic","ionic framework":"Ionic","jquery":"jQuery","JQuery":"jQuery","JQUERY":"jQuery","laravel":"Laravel","meteor":"Meteor","meteor js":"Meteor","meteorjs":"Meteor","MeteorJS":"Meteor","nestjs":"NestJS","nest js":"NestJS","Nest JS":"NestJS","Nestjs":"NestJS","next js":"Next.js","Next js":"Next.js","next.js":"Next.js","nextjs":"Next.js","NextJS":"Next.js","node":"Node.js","Node":"Node.js","node.js":"Node.js","nodejs":"Node.js","NodeJS":"Node.js","nuxt js":"Nuxt.js","Nuxt js":"Nuxt.js","nuxt.js":"Nuxt.js","nuxtjs":"Nuxt.js","NuxtJS":"Nuxt.js","phoenix":"Phoenix","Phoenix framework":"Phoenix","pytorch":"PyTorch","Pytorch":"PyTorch","torch":"PyTorch","Torch":"PyTorch","react":"React","react.js":"React","React.js":"React","reactjs":"React","ReactJS":"React","react native":"React Native","ReactNative":"React Native","reactnative":"React Native","rn":"React Native","RN":"React Native","rails":"Ruby on Rails","Rails":"Ruby on Rails","ror":"Ruby on Rails","ROR":"Ruby on Rails","ruby on rails":"Ruby on Rails","Ruby On Rails":"Ruby on Rails","spark":"Apache Spark","Spark":"Apache Spark","spring":"Spring Boot","Spring":"Spring Boot","spring boot":"Spring Boot","Spring Boot":"Spring Boot","spring framework":"Spring Boot","Spring Framework":"Spring Boot","SpringBoot":"Spring Boot","springboot":"Spring Boot","svelte":"Svelte","symfony":"Symfony","tailwind":"Tailwind CSS","Tailwind":"Tailwind CSS","tailwind css":"Tailwind CSS","Tailwind Css":"Tailwind CSS","tailwindcss":"Tailwind CSS","TailwindCSS":"Tailwind CSS","tensorflow":"TensorFlow","Tensorflow":"TensorFlow","tensor flow":"TensorFlow","Vue":"Vue.js","vue":"Vue.js","vue js":"Vue.js","vue.js":"Vue.js","vuejs":"Vue.js","VueJS":"Vue.js","xamarin":"Xamarin","Xamarin Forms":"Xamarin","Xamarin.forms":"Xamarin","livewire":"Livewire","phpunit":"PHPUnit","alpine":"Alpine.js","alpine js":"Alpine.js","alpinejs":"Alpine.js","filament":"Filament","docker":"Docker","kubernetes":"Kubernetes","k8s":"Kubernetes","github":"GitHub","gitlab":"GitLab","bitbucket":"Bitbucket","terraform":"Terraform","puppet":"Puppet","chef":"Chef","git":"Git","jenkins":"Jenkins","kafka":"Kafka","rabbitmq":"RabbitMQ","amazon sqs":"Amazon SQS","amqp":"AMQP","pubsub":"PubSub","rest api":"REST API","restful api":"RESTful APIs","restful apis":"RESTful APIs","graphql":"GraphQL","ansible":"Ansible","vagrant":"Vagrant","vault":"Vault","consul":"Consul","prometheus":"Prometheus","grafana":"Grafana","elk stack":"ELK Stack","splunk":"Splunk","scrum":"Scrum","agile":"Agile","kanban":"Kanban","devops":"DevOps","ci\/cd":"CI\/CD","tdd":"TDD","bdd":"BDD","linux":"Linux","windows":"Windows","macos":"macOS","ubuntu":"Ubuntu","centos":"CentOS","debian":"Debian","junit":"JUnit","pytest":"PyTest","jest":"Jest","mocha":"Mocha","cypress":"Cypress","selenium":"Selenium","html":"HTML","HTML":"HTML","html5":"HTML","HTML5":"HTML","css":"CSS","CSS":"CSS","css3":"CSS","CSS3":"CSS","sass":"Sass","scss":"Sass","SCSS":"Sass","less":"Less","LESS":"Less","webpack":"Webpack","gulp":"Gulp","npm":"npm","yarn":"Yarn","sql":"SQL","full time":"Fuldtid","full-time":"Fuldtid","fuldtid":"Fuldtid","part time":"Deltid","part-time":"Deltid","deltid":"Deltid","contract":"Kontrakt","kontrakt":"Kontrakt","remote":"Fjernarbejde","fjernarbejde":"Fjernarbejde","hybrid":"Hybridarbejde","hybridarbejde":"Hybridarbejde","on-site":"Fysisk tilstedeværelse","onsite":"Fysisk tilstedeværelse","fysisk tilstedeværelse":"Fysisk tilstedeværelse"}
}

## TASK:
1. **Extract ALL coding languages and frameworks** mentioned in the job description
2. **Use the skill_aliases mapping** to normalize skill names (e.g., "JS" → "JavaScript", "React.js" → "React")
3. **Only include skills from the coding_categories** (languages and frameworks)
4. **Avoid duplicates** - if "JavaScript" and "JS" are both mentioned, only include "JavaScript"
5. **Be thorough** - look for skills mentioned in:
   - Job title
   - Job description
   - Brief summary
   - Requirements sections
   - Nice-to-have sections

## SKILL CATEGORIES TO EXTRACT:
- **Languages**: Programming languages (PHP, Python, JavaScript, Java, C#, Go, Rust, etc.)
- **Frameworks**: Web frameworks and libraries (Laravel, React, Vue.js, Angular, Django, Spring Boot, etc.)
- **Databases**: Database systems and data stores (MySQL, PostgreSQL, Redis, MongoDB, DynamoDB, etc.)
- **Tools**: Development tools and infrastructure (Git, Docker, AWS, CI/CD, Jenkins, Kafka, etc.)

## EXCLUSION RULES:
- Do NOT extract general skills (communication, languages like English, etc.)
- Do NOT extract business skills (Excel, PowerBI for non-technical roles)
- Do NOT extract work arrangements (remote, physical presence)
- Do NOT include methodologies (Agile, Scrum, etc.) unless specifically technical
- Do NOT include skills already in existing_skills_from_database

## OUTPUT FORMAT:
Return ONLY valid JSON in this exact structure:
{
  "job_id": <integer>,
  "extracted_skills": [
    {
      "skill_name": "<normalized_skill_name>",
      "category": "<languages|frameworks|databases|tools>",
      "confidence": <integer 0-100>,
      "mentioned_as": ["<original_mention_1>", "<original_mention_2>"],
      "context": "<brief_context_where_found>"
    }
  ],
  "reasoning": {
    "total_skills_found": <integer>,
    "skills_by_category": {
      "languages": ["<skill1>", "<skill2>"],
      "frameworks": ["<skill1>", "<skill2>"],
      "databases": ["<skill1>", "<skill2>"],
      "tools": ["<skill1>", "<skill2>"]
    },
    "duplicates_removed": ["<original_mention> → <normalized_name>"],
    "excluded_skills": ["<skill>", "<reason>"]
  },
  "confidence": <integer 0-100>
}

Return nothing outside the JSON object.
Fuld AI Svar:
{
  "job_id": 4449,
  "extracted_skills": [
    {
      "skill_name": "Python",
      "category": "languages",
      "confidence": 100,
      "mentioned_as": ["Python"],
      "context": "Our stack: Python, PostgreSQL, BigQuery, and GCP."
    },
    {
      "skill_name": "PostgreSQL",
      "category": "databases",
      "confidence": 100,
      "mentioned_as": ["PostgreSQL"],
      "context": "Our stack: Python, PostgreSQL, BigQuery, and GCP."
    },
    {
      "skill_name": "BigQuery",
      "category": "databases",
      "confidence": 100,
      "mentioned_as": ["BigQuery"],
      "context": "Our stack: Python, PostgreSQL, BigQuery, and GCP."
    },
    {
      "skill_name": "GCP",
      "category": "tools",
      "confidence": 100,
      "mentioned_as": ["GCP", "Google Cloud Platform"],
      "context": "Our stack: Python, PostgreSQL, BigQuery, and GCP."
    }
  ],
  "reasoning": {
    "total_skills_found": 4,
    "skills_by_category": {
      "languages": ["Python"],
      "frameworks": [],
      "databases": ["PostgreSQL", "BigQuery"],
      "tools": ["GCP"]
    },
    "duplicates_removed": [],
    "excluded_skills": []
  },
  "confidence": 100
}
Ansøgning
Ansøgning (Dansk)
Generer Ansøgning

Brug avanceret AI (GPT-4o) til at generere en personaliseret ansøgning på dansk til denne jobansøgning. Brevet vil være skræddersyet til din profil, de specifikke jobkrav og omfattende virksomhedsinformation for maksimal effekt.

Jobbeskrivelse

About the job

We’ve built a system that predicts various signals about the electricity system on a 72 hour horizon, worldwide. Now we’re in the process of expanding the dimensions, horizons, and granularity of our forecasts. We’re building a platform that can generate high-quality forecasts without requiring bespoke engineering effort for each signal or geographical area.

To help us move quickly, we’re looking for an experienced data engineer to join our team. Our ideal candidate has scaled ML systems and designed pipelines for large-scale time series data, supporting all stages of the model life cycle while keeping complexity low.

We’re looking for an experienced Data Engineer who thrives on tackling complex scaling challenges, enjoys collaborating and isn’t afraid to get hands-on with implementation.

About Electricity Maps 🌎

Electricity Maps is on a mission to accelerate the transition to a decarbonized electricity system. Our platform provides real-time and forecasted electricity data, helping companies like Google and Cisco to unlock flexibility and reduce emissions.

Our free map product is used by millions of people around the world

Our API powers products at some of the world’s largest enterprises

We’re backed by top-tier investors with deep experience scaling developer-first, climate-focused companies

What You’ll Build and Own 🧱

You’ll work on data pipelines, feature stores, and ML infrastructure that is flexible enough to predict multiple signals in over 350 regions around the world.

Today, Our Signals Are

Load

Day-ahead prices

Carbon intensity

Renewable energy %

Electricity mix (all generation sources)

We have the vision to keep adding more signals and features to our forecasting platform such as: balancing prices and curtailment.

You’ll

Shape and build solutions with our lead and other engineers on the team

Ship fast, iterate based on real feedback, and own your work in production

Refine how we build, deploy, and scale across the stack

You’ll Thrive Here If You… 🔍

Have built ML systems at scale (feature stores, model registries, experimentation → training → inference → monitoring)

Have experience with time series forecasting and handling millions of data points

Balance pragmatism with ambition: scoping to fit the appetite, not over-engineering

Enjoy fast-paced, high-impact cycles and making product/technical decisions independently

Care about usability, performance, and delivering real value to users

Mentor colleagues, spar with peers, and raise the team’s overall level

Our stack: Python, PostgreSQL, BigQuery, and GCP. No need for exact matches 🫶🏻 just be comfortable working across modern data platforms.

Bonus points if you…

Bring experience from the energy domain

Role Details📍

Full-time

Based in Copenhagen

Competitive salary + stock options

6 weeks vacation + full health insurance

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