AdTechTalent
Data Science105 days agoHybrid

Klever

Data Engineer / Ingénieur ( e) de données

pythonsqlgoogle cloudbigqueryvertex aifirestoremlopsaidata engineeringbatch processingdockerterraformtensorflowpytorchmachine learningdistributed computingprogrammatic advertising

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Mid-level

Years experience

3-5

Location

Montréal, Canada

Full job description

Data Engineer role at Klever Programmatic based in Montreal office with hybrid work arrangement. Responsibilities include collaborating with data scientists, domain experts, and software engineers to understand data needs and provide infrastructure; implementing data pipelines for preprocessing, cleaning, and preparing large datasets for AI agents and platform visualizations; working with agent communication and data access patterns such as Agent2Agent (A2A) and MCP; building data pipelines on Google Cloud using BigQuery, Vertex AI, Firestore, external APIs, and other cloud services; developing APIs and MCPs for model-serving and LLM-powered systems. Requirements include minimum 3 years experience implementing AI solutions, knowledge of MLOps/AI platforms, proficiency in Python, familiarity with SQL and data modeling, strong data manipulation and preprocessing skills, experience with batch data processing and orchestration, software development best practices including Git and agile methodologies, understanding of data storage formats like JSON and parquet, knowledge of ML/AI concepts, and interest in coding agents such as Claude Code, Codex, and Copilot. Nice to have skills include Kedro, LangChain, CrewAI, TensorFlow, PyTorch, Terraform, Docker, big data technologies, distributed computing, and domain knowledge in advertising and marketing. Soft skills required are strong communication, creative problem solving, ability to work in fast-paced agile environment, self-motivation, teamwork, attention to detail, and organizational skills.

What you'll do

  • 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 facilitate preprocess, clean, and prepare large datasets for various purposes: feeding AI agents and platform visualizations
  • Work with agent communication and tool/data access patterns (e.g. Agent2Agent (A2A), MCP, agent skills, or similar emerging standards)
  • Build data pipelines hosted in Google Cloud with technologies like BigQuery, Vertex AI, Firestore (NoSQL database), external APIs and other cloud services
  • Develop APIs and MCPs for model-serving and LLM-powered systems

Requirements

  • Minimum of 3 years of hands-on experience in implementing AI solutions
  • Proven knowledge of MLOps/AI platforms and workflows in real-world applications
  • Proficiency in the Python programming language
  • Familiarity with SQL and data modelling principles
  • Strong understanding of data manipulation, feature engineering, and data preprocessing techniques
  • Experience with developing batch data processing applications, monitoring data processing applications and orchestrating data processing applications
  • Familiarity with software development best practices, version control systems (Git), and agile methodologies
  • Understanding of different data storage formats (JSON, parquet, etc.)
  • Good knowledge of concepts and best practices related to ML/AI
  • Proficiency and interest in using coding agents: Claude Code, Codex, Copilot, etc.

Tech stack

PythonSQLGoogle CloudBigQueryVertex AIFirestoreAPIsMCPLLMGitKedroLangChainCrewAITensorFlowPyTorchTerraformDockerBig DataDistributed Computing

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