AI & Data Engineer

Technology, Data & Digital · Data, AI & Analytics · Data Engineering · Machine Learning · Artificial Intelligence

In short

We are seeking an AI & Data Engineer to join our AI & Data team in Copenhagen. This role involves building data pipelines and platforms for analytics and AI, as well as developing AI-powered features using LLMs and RAG. You will work in a multidisciplinary team to solve complex business challenges for clients using data and AI.

Responsibilities

Build, test, and maintain data pipelines for ingesting, moving, and transforming data.
Prepare, clean, and model data for analytics, reporting, machine learning, and Generative AI.
Develop on cloud data platforms (Azure, AWS, Google Cloud) using services like Databricks, Azure Data Factory, Snowflake, Fabric.
Utilize distributed processing and streaming tools like Spark and Kafka.
Build and integrate GenAI-powered features including RAG pipelines, prompt engineering, and agent workflows.
Integrate with LLM provider APIs (e.g., OpenAI, Anthropic, Azure OpenAI).
Support deployment and monitoring of AI/ML models in production (MLOps).
Ensure data quality, validation, and monitoring.
Support deployment of data and AI solutions using version control, CI/CD, and infrastructure-as-code.
Collaborate with colleagues and client stakeholders to translate requirements into technical solutions.
Stay current on developments in data engineering, cloud platforms, and GenAI/LLM tooling.

Requirements

2–3 years of hands-on experience in data engineering or applied AI/ML engineering.
University coursework, thesis work, internships, or graduate programs focused on computer science, software engineering, data engineering, or related fields.
Experience building data pipelines, databases, APIs, or cloud applications.
Exposure to cloud platforms, open-source data tools, or software development practices.
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Data Science, Mathematics, Physics, Engineering, or a related field.
Solid programming skills in Python and SQL.
Hands-on experience building with LLMs (e.g., RAG pipelines, prompt engineering, agent frameworks, or integrating LLM provider APIs).
Working knowledge of core data concepts: relational databases, data modeling, ETL/ELT processes.
Strong, structured problem-solving and debugging skills.
Ability to explain technical work clearly to both technical and non-technical colleagues.
Strong teamwork and collaboration skills.
Fluency in English.

Desired Qualifications

Scala or Java a plus.
Hands-on experience with a cloud platform (Azure, AWS, or Google Cloud), ideally including data services.
Experience with Spark, Databricks, Kafka, Airflow, dbt, or similar data engineering tools.
Familiarity with Git, Docker, CI/CD pipelines, or infrastructure-as-code tools such as Terraform.
Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar.
Interest in data architecture concepts such as lakehouses, medallion architecture, data mesh, or data governance.
Relevant certifications (e.g. Databricks Data Engineer Associate, AWS Data Engineer, Claude etc.).
Danish language skills are an advantage for local roles.

Benefits

Opportunities to keep skills relevant through certifications, learning, and diverse work experiences.
Support for people’s physical, mental, and financial health.
Inclusive and diverse environment where everyone feels a sense of belonging and is respected and empowered.
Work at the heart of change.
Recognized as one of the World’s Best Workplaces™.

Skills

PythonSQLLLMsRAGSparkKafkaGitDockerTerraformScikit-learnTensorFlowPyTorch

#AI#Data Engineering#LLM#RAG#Generative AI#Python#SQL#Cloud#Azure#AWS#GCP#Databricks#Snowflake#Fabric#Spark#Kafka#MLOps

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