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 join GenAI application teams supporting products across search, conversational AI, and customer support. Sitting at the intersection of analytics, product, and engineering, you'll transform complex data into actionable insights that directly influence product performance and business decisions.This is not a traditional Data Engineering role focused on building data platforms or infrastructure. Instead, we're looking for someone with a strong analytical and product mindset who enjoys solving business problems through data, defining meaningful metrics, and delivering insights that improve AI-powered products.You'll own analytical domains end-to-end, partnering closely with Product Managers, Data Scientists, and Software Engineers to ensure data is accurate, well-modelled, measurable, and actionable.ResponsibilitiesOwn analytical data domains from end to end, ensuring data quality, accuracy, consistency, and reliabilityDesign and develop scalable analytical data models and reusable datasets that support business decision-makingTransform large, complex datasets into actionable insights that influence product strategy and customer experienceDefine and track meaningful product metrics, KPIs, and success measures for AI applicationsBuild dashboards and monitoring solutions covering product performance, model quality, operational health, and costAnalyse A/B tests, experiments, model performance, and LLM evaluation outputs to generate business insightsConduct ad hoc investigations and proactively identify optimisation opportunities through dataCollaborate with Product, Data Science, and Engineering teams to define analytical solutions for complex business challengesWork with structured and unstructured datasets, including text, LLM outputs, and telemetry dataMaintain the health and performance of analytical datasets and pipelines through monitoring and optimisationDesired Skills and ExperienceExpert-level SQL skills within analytical or large-scale data environmentsStrong Python and/or PySpark experience for data manipulation and large-scale analysisExcellent data modelling skills and understanding of modern analytical data warehouse practicesProven experience owning analytical domains from data modelling through to reporting, experimentation, and stakeholder insightsStrong product mindset with the ability to define metrics, answer business questions, and influence product decisions through dataExperience analysing experiments, customer behaviour, or product performance in a product-focused environmentComfortable working with machine learning or AI-related datasets, including model evaluation and error analysisExperience working with unstructured or free-text data is highly advantageousFamiliarity with tools such as dbt, Snowflake, Streamlit, or Airflow is beneficialExcellent communication skills with experience presenting analytical findings to technical and non-technical stakeholdersSummary of the Best CandidateThe ideal candidate is an Analytics Engineer or highly technical Data Analyst rather than a traditional Data Engineer. You'll combine strong technical skills with commercial awareness, using data to answer product questions, define meaningful metrics, and drive measurable business outcomes.Successful candidates will typically have experience owning analytics end-to-end, including:Data modelling and dataset designData quality and governanceDashboarding and monitoringExperimentation and performance analysisStakeholder-facing analytics and business problem solvingWhile strong technical skills are essential, approximately two-thirds of the role focuses on analytics, product thinking, and business impact, with the remaining one-third centred on data engineering and data modelling. Candidates should therefore be equally comfortable discussing technical implementation and explaining how their work influenced product or business decisions.