Analytics Engineer

emagine is looking for an Analytics Engineer.

Start: ASAP
Duration: 7 months with possibility of extension
Location: Stockholm (3 days per week on-site)

We are looking for an AI Data Foundations Engineer to join a highly skilled data and analytics team. In this role, you will be responsible for building trusted, scalable, and reusable data products that support analytics, machine learning, and AI-driven solutions across the business.

The role combines analytics engineering, data engineering, and AI enablement. You will work closely with stakeholders across data, product, and engineering teams to transform structured and unstructured data into reliable, analytics-ready and AI-ready assets. The focus is on creating strong data foundations that enable better decision-making, self-service analytics, and future AI initiatives.

Key Responsibilities

• Build a strong understanding of business processes and data domains to support stakeholders with trusted and governed data access.

• Identify, analyze, and prepare data from multiple sources for analytics and AI use cases.

• Design and develop scalable data models, data products, and data flows that support reporting, analytics, machine learning, semantic search, copilots, and AI-powered applications.

• Build and maintain automated pipelines that transform raw data into high-quality, enriched, and reliable datasets.

• Establish and maintain reusable metrics, semantic models, metadata, lineage, and data quality frameworks.

• Drive improvements in the data platform by developing reusable components, ingestion frameworks, and capabilities that support both structured and unstructured data.

• Collaborate closely with analytics engineers, data engineers, data scientists, AI engineers, analysts, and business stakeholders to deliver solutions aligned with business needs.

Required Experience

• Experience working as an Analytics Engineer, Data Engineer, or in a similar role within large-scale enterprise environments.

• Strong understanding of data modeling, data transformation, and analytics engineering principles.

• Experience building and maintaining modern data pipelines and data products.

• Ability to work closely with business stakeholders and translate requirements into scalable technical solutions.

• Experience working with structured and unstructured data.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.

Preferred Experience

• Proven track record of delivering impactful analytics solutions and reusable data products.

• Experience preparing data for AI-related use cases such as semantic search, retrieval-augmented generation (RAG), copilots, agents, or knowledge management solutions.

• Strong business understanding and the ability to connect business challenges with data and AI opportunities.

• Knowledge of data governance, metadata management, data lineage, observability, DataOps, DevOps, and Responsible AI principles.

• Strong problem-solving skills combined with a collaborative and proactive mindset.

• Experience from a product-focused, digital, or consumer-facing business is highly valued.

• Interest in or experience from the gaming industry is considered a strong advantage.

What we're looking for

You are someone who enjoys solving complex data challenges and building scalable foundations that others can rely on. You combine strong technical skills with a business-oriented mindset and are comfortable working across multiple teams and disciplines. Experience working with both analytics and AI-driven initiatives will be highly beneficial in this role.