Ingénieur ( e) de données- Data Engineer
- Montreal, QC, Canada
Full-time
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Job details
- Job type
- Full-time
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- Posting language
- English · French
- Posted
Original job description
English section of this bilingual listing.
Data Engineer
WE ARE KLEVER
Take a bold step in your career by joining the team at Klever Programmatic, a global leader in programmatic advertising solutions and one of the fastest growing companies in North America. Klever allows advertisers and agencies of all sizes to advertise on a wide array of digital programmatic channels (display, video, CTV, programmatic audio, DOOH, native, mobile…). Programmatic advertising is a complex and fast-growing field where expertise like Klever’s is scarce and essential.
Summary
Join our team of data and AI specialists and build the data foundation that powers our AI agents and the models that predict advertiser campaign outcomes across industries. You’ll design pipelines on Google Cloud and give agents access to data through APIs and MCP servers. No ad tech background needed: we’ll teach you the industry. This role is hybrid, based in our Montreal office.
Job Description
- Collaborate with cross-functional teams, including data scientists, domain experts, and software engineers, to understand data requirements and provide the necessary infrastructure and support.
- Implement data pipelines that preprocess, clean, and prepare large datasets for various purposes: feeding AI agents and our data science models.
- Work with agent communication and tool/data access patterns (e.g. Agent2Agent (A2A), MCP, agent skills, or similar emerging standards). These standards are new for everyone, so we’ll learn them together.
- Build data pipelines hosted in Google Cloud with technologies like BigQuery, Apache NiFi, Vertex AI, Firestore (NoSQL database), external APIs and other cloud services.
- Develop APIs and MCP servers for model-serving and LLM-powered systems.
Qualifications
Required experience and skills
- Hands-on experience in implementing data engineering solutions.
- Proficiency in Python, and good knowledge of SQL and data modelling principles.
- Strong data manipulation and preprocessing skills, including feature engineering and common storage formats (JSON, Parquet, etc.).
- Experience building, orchestrating and monitoring batch data processing applications.
- Familiarity with software development best practices, version control systems (Git), and agile methodologies.
- Interest in using coding agents like Claude Code and Codex.
We encourage you to apply even if you don't check every single box. If you're excited about this role and your experience doesn't align perfectly, we still want to hear from you.
Nice to Have
- Familiarity with Apache NiFi, Kedro, LangChain, TensorFlow and/or PyTorch.
- Good understanding of ML/AI concepts and best practices, and of how data supports models in production.
- Infrastructure-as-code (Terraform) and containerization (Docker).
- Hands-on experience with MLOps/AI platforms, or with machine learning models and algorithms that address complex business challenges.
- Experience with big data technologies and distributed computing.
- Domain knowledge about the advertising and marketing industries.
- Knowledge of Google Cloud and BigQuery (equivalent experience on AWS or Azure is also welcome).
- Experience with coding agents.
Soft skills
- Strong communication skills.
- Creative thinker with excellent problem solving abilities.
- Self-motivated, entrepreneurial and detail-oriented; comfortable working independently or as part of a team in an agile environment.
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Ingénieur·e en données (Data Engineer)
Read the full bilingual original
Data Engineer
WE ARE KLEVER
Take a bold step in your career by joining the team at Klever Programmatic, a global leader in programmatic advertising solutions and one of the fastest growing companies in North America. Klever allows advertisers and agencies of all sizes to advertise on a wide array of digital programmatic channels (display, video, CTV, programmatic audio, DOOH, native, mobile…). Programmatic advertising is a complex and fast-growing field where expertise like Klever’s is scarce and essential.
Summary
Join our team of data and AI specialists and build the data foundation that powers our AI agents and the models that predict advertiser campaign outcomes across industries. You’ll design pipelines on Google Cloud and give agents access to data through APIs and MCP servers. No ad tech background needed: we’ll teach you the industry. This role is hybrid, based in our Montreal office.
Job Description
- Collaborate with cross-functional teams, including data scientists, domain experts, and software engineers, to understand data requirements and provide the necessary infrastructure and support.
- Implement data pipelines that preprocess, clean, and prepare large datasets for various purposes: feeding AI agents and our data science models.
- Work with agent communication and tool/data access patterns (e.g. Agent2Agent (A2A), MCP, agent skills, or similar emerging standards). These standards are new for everyone, so we’ll learn them together.
- Build data pipelines hosted in Google Cloud with technologies like BigQuery, Apache NiFi, Vertex AI, Firestore (NoSQL database), external APIs and other cloud services.
- Develop APIs and MCP servers for model-serving and LLM-powered systems.
Qualifications
Required experience and skills
- Hands-on experience in implementing data engineering solutions.
- Proficiency in Python, and good knowledge of SQL and data modelling principles.
- Strong data manipulation and preprocessing skills, including feature engineering and common storage formats (JSON, Parquet, etc.).
- Experience building, orchestrating and monitoring batch data processing applications.
- Familiarity with software development best practices, version control systems (Git), and agile methodologies.
- Interest in using coding agents like Claude Code and Codex.
We encourage you to apply even if you don't check every single box. If you're excited about this role and your experience doesn't align perfectly, we still want to hear from you.
Nice to Have
- Familiarity with Apache NiFi, Kedro, LangChain, TensorFlow and/or PyTorch.
- Good understanding of ML/AI concepts and best practices, and of how data supports models in production.
- Infrastructure-as-code (Terraform) and containerization (Docker).
- Hands-on experience with MLOps/AI platforms, or with machine learning models and algorithms that address complex business challenges.
- Experience with big data technologies and distributed computing.
- Domain knowledge about the advertising and marketing industries.
- Knowledge of Google Cloud and BigQuery (equivalent experience on AWS or Azure is also welcome).
- Experience with coding agents.
Soft skills
- Strong communication skills.
- Creative thinker with excellent problem solving abilities.
- Self-motivated, entrepreneurial and detail-oriented; comfortable working independently or as part of a team in an agile environment.
-
Ingénieur·e en données (Data Engineer)
NOUS SOMMES KLEVER
Faites un pas audacieux dans votre carrière en rejoignant l’équipe de Klever Programmatic, un leader mondial des solutions de publicité programmatique et l’une des entreprises à la croissance la plus rapide en Amérique du Nord.
Klever permet aux annonceurs et aux agences de toutes tailles de diffuser des campagnes sur un large éventail de canaux numériques programmatiques (display, vidéo, CTV, audio programmatique, DOOH, native, mobile…).
La publicité programmatique est un domaine complexe et en forte croissance où une expertise comme celle de Klever est à la fois rare et essentielle.
Sommaire
Joignez-vous à notre équipe de spécialistes en données et en IA pour bâtir l’infrastructure de données qui alimente nos agents IA et les modèles qui prédisent les résultats des campagnes des annonceurs, tous secteurs confondus. Vous concevrez des pipelines sur Google Cloud et donnerez aux agents accès aux données au moyen d’API et de serveurs MCP. Aucune expérience en technologie publicitaire n’est requise : nous vous initierons au domaine.
Ce poste est hybride et basé à notre bureau de Montréal.
Description du poste
- Collaborer avec des équipes multidisciplinaires, incluant des scientifiques des données, experts métier et ingénieurs logiciels, afin de comprendre les besoins en données et fournir l’infrastructure et le support nécessaires.
- Mettre en place des pipelines de données permettant le prétraitement, le nettoyage et la préparation de grands ensembles de données à différentes fins : alimentation d’agents IA et de nos modèles de science des données.
- Travailler avec des modèles de communication entre agents et des schémas d’accès aux outils/données (ex. : Agent2Agent (A2A), MCP, compétences d’agents ou standards émergents similaires). Ces standards sont nouveaux pour tout le monde : nous les apprendrons ensemble.
- Construire des pipelines de données hébergés sur Google Cloud à l’aide de technologies telles que BigQuery, Apache NiFi, Vertex AI, Firestore (base de données NoSQL), API externes et autres services cloud.
- Développer des API et des serveurs MCP pour des systèmes de mise en service de modèles et des systèmes propulsés par des LLM.
Qualifications
Expérience et compétences techniques requises
- Expérience pratique dans la mise en œuvre de solutions d’ingénierie des données.
- Maîtrise de Python et bonne connaissance du SQL et des principes de modélisation de données.
- Solide maîtrise de la manipulation et du prétraitement des données, incluant l’ingénierie des caractéristiques (feature engineering) et les formats de stockage courants (JSON, Parquet, etc.).
- Expérience dans le développement, l’orchestration et la surveillance d’applications de traitement de données par lots.
- Familiarité avec les bonnes pratiques de développement logiciel, les systèmes de contrôle de version (Git) et les méthodologies agiles.
- Intérêt pour les agents de codage comme Claude Code et Codex.
Nous vous encourageons à postuler même si vous ne remplissez pas tous les critères. Si ce poste vous enthousiasme, mais que votre expérience ne correspond pas parfaitement, nous aimerions quand même recevoir votre candidature.
Atouts
- Connaissance d’Apache NiFi, Kedro, LangChain, TensorFlow et/ou PyTorch.
- Bonne compréhension des concepts et des meilleures pratiques en ML/IA, ainsi que du rôle des données dans les modèles en production.
- Connaissance de l’infrastructure en tant que code (Terraform) et de la conteneurisation (Docker).
- Expérience pratique avec des plateformes MLOps/IA, ou avec des modèles et algorithmes d’apprentissage automatique appliqués à des enjeux d’affaires complexes.
- Expérience avec les technologies Big Data et le calcul distribué.
- Connaissance du domaine de la publicité et du marketing.
- Connaissance de Google Cloud et de BigQuery (une expérience équivalente sur AWS ou Azure est aussi la bienvenue).
- Expérience avec les agents de codage.
Compétences interpersonnelles
- Excellentes aptitudes en communication.
- Esprit créatif et fortes capacités de résolution de problèmes.
- Autonomie, esprit entrepreneurial et sens du détail; à l’aise pour travailler de manière indépendante comme en équipe, dans un environnement agile.
More about this job
Responsibilities
Build and maintain cloud-hosted data pipelines that clean and prepare large datasets for AI agents and data science models. Collaborate with data scientists, domain experts, and software engineers, and develop APIs and MCP servers to provide data access and support model-serving and LLM-powered systems.
Requirements
Candidates need hands-on data engineering experience, proficiency in Python, and a good understanding of SQL, data modeling, data preprocessing, and batch processing. Familiarity with software development practices, Git, and agile methods is expected; experience with cloud, AI/ML, and the listed preferred tools is an advantage.
Skills
- Python
- SQL
- Data Modeling
- Data Engineering
- Data Preprocessing
- Feature Engineering
- Batch Processing
- Data Pipeline Orchestration
- Google Cloud
- BigQuery
- Apache NiFi
- API Development
- MCP Servers
- Git
- Agile Methodologies
- Machine Learning
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
- Marketing
Keywords
- Data Engineering
- Python
- SQL
- Data Modeling
- Data Pipelines
- Data Preprocessing
- Feature Engineering
- Batch Processing
- Google Cloud
- BigQuery
- Apache NiFi
- Vertex AI
- Firestore
- APIs
- MCP Servers
- Agent2Agent (A2A)
- AI Agents
- Large Language Models (LLMs)
- Machine Learning
- MLOps
- Kedro
- LangChain
- TensorFlow
- PyTorch
- Terraform
- Docker
- Git
- Agile Methodologies
- Big Data
- Distributed Computing