Data Analytics Engineer

Data Analytics Engineer | SQL, Python/PySpark, Data Modelling

Up to €110 per hour (based on a 40-hour week)

Hybrid working- 2 days per week onsite in Amsterdam, Netherlands

Initial contract until 31st December 2026

About the Client

Digital Skills are working with a global technology business at the forefront of AI innovation. The organisation is delivering cutting-edge generative AI applications across multiple products, focused on improving customer experiences through data-driven insights and intelligent systems.

About the Role

This is an exciting opportunity for a Data Analytics Engineer to work within GenAI application teams, supporting areas such as search, conversational AI, and customer support tools. The role sits at the intersection of analytics and application logic, focusing on transforming complex data into actionable insights that directly influence product performance.

Responsibilities

• Own end-to-end data domains, ensuring quality, accuracy, and consistency
• Design and develop scalable analytical data models and reusable datasets
• Transform large and complex datasets into actionable insights and visualisations
• Build monitoring, quality, and cost dashboards for AI applications
• Analyse experiments, model performance, and LLM evaluation outputs
• Conduct ad hoc investigations and proactively identify optimisation opportunities
• Collaborate with product, data science, and engineering teams to define analytical solutions
• Work with unstructured data including text, LLM outputs, and telemetry data
• Maintain data pipeline health through monitoring and performance tuning

Desired Skills and Experience

• Strong SQL expertise in analytical or large-scale data environments
• Hands-on experience with Python and/or PySpark for data manipulation
• Solid experience in data modelling and modern data warehouse practices
• Experience working in product-focused or customer-facing analytics environments
• Ability to generate insights beyond surface-level metrics and drive business impact
• Exposure to machine learning or AI-driven datasets, including evaluation and error analysis
• Experience working with unstructured or free-text data is highly advantageous
• Familiarity with tools such as dbt, Snowflake, Streamlit, or Airflow is beneficial
• Strong communication skills and ability to work with cross-functional teams

Summary of the Best Candidate

The ideal candidate will have previous experience in analytics or data-focused roles, with a strong emphasis on SQL, Python, and data modelling. They will bring a business-oriented mindset, able to translate complex datasets into meaningful insights that support product decisions.

This role suits someone proactive and curious, who takes ownership of data domains and thrives in ambiguous environments. Experience working with AI or machine learning data, particularly in customer-facing or product environments, will be a significant advantage.