Data Analytics Engineer

Data Analytics Engineer | SQL, Python/PySpark, Data ModellingUp to €110 per hour (based on a 40-hour week)Hybrid working- 2 days per week onsite in Amsterdam, NetherlandsInitial contract until 31st December 2026About the ClientDigital 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 RoleThis 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.ResponsibilitiesOwn end-to-end data domains, ensuring quality, accuracy, and consistencyDesign and develop scalable analytical data models and reusable datasetsTransform large and complex datasets into actionable insights and visualisationsBuild monitoring, quality, and cost dashboards for AI applicationsAnalyse experiments, model performance, and LLM evaluation outputsConduct ad hoc investigations and proactively identify optimisation opportunitiesCollaborate with product, data science, and engineering teams to define analytical solutionsWork with unstructured data including text, LLM outputs, and telemetry dataMaintain data pipeline health through monitoring and performance tuningDesired Skills and ExperienceStrong SQL expertise in analytical or large-scale data environmentsHands-on experience with Python and/or PySpark for data manipulationSolid experience in data modelling and modern data warehouse practicesExperience working in product-focused or customer-facing analytics environmentsAbility to generate insights beyond surface-level metrics and drive business impactExposure to machine learning or AI-driven datasets, including evaluation and error analysisExperience working with unstructured or free-text data is highly advantageousFamiliarity with tools such as dbt, Snowflake, Streamlit, or Airflow is beneficialStrong communication skills and ability to work with cross-functional teamsSummary of the Best CandidateThe 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.