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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analytics Engineer (GenAI Application Team) - **Company:** Huxley Associates - **Location:** Amsterdam, Netherlands - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Big Data, Information Engineering, Data Governance, Data Infrastructure, Data Warehousing, Relational Databases, Database Queries, Python (Programming Language), Performance Tuning, Software Product Management, Technical Data Management Systems, Unstructured Data, Data Logging, Data Classification, Large Language Models, Snowflake, Pyspark, Data Analytics, Streamlit Framework, Data Pipelines - **Published:** September 26, 2026 - **Apply:** https://www.huxley.com/en-gb/job/data-analytics-engineer-genai-application-team/4068628 ## About the Role * 3+ years of experience in analytics, data, or software-adjacent roles working with large-scale data systems. * Strong business orientation and customer-focused mindset. * Ability to independently navigate ambiguity, prioritize based on impact, and drive initiatives end-to-end. * Strong analytical thinking and ability to derive meaningful insights. * Experience supporting production environments and delivering high-impact insights. * Experience in ML/AI product environments, evaluation workflows, or model/error analysis is a strong plus. * Resourceful and thoughtful use of AI tools and assistants. Technical Skills * Strong SQL skills and experience working with relational databases in analytical environments. * Hands-on experience with Python and PySpark. * Strong experience with data modeling and modern Data Warehouse practices. * Experience building maintainable, reusable, production-grade analytical code and transformations. * Experience working with free text, unstructured data, LLM-generated outputs, and AI application telemetry. * Nice to have: + dbt + Snowflake + Streamlit + Airflow + Argo * Nice to have: AI/LLM-related datasets and evaluation pipelines experience. Collaboration & Communication * Excellent communication skills. * Ability to explain technical concepts to non-technical stakeholders. * Proven cross-functional collaboration with product, engineering, analytics, and data science teams. * Self-driven and comfortable owning ambiguous problem spaces. ## Description * Looking for candidates with a stronger analytics and product mindset than a traditional Data Engineering profile. * Former Senior Data Engineers or Data Architects focused primarily on infrastructure and platform development are unlikely to be a strong fit. * The role is not centered on building data infrastructure from scratch. * Focus areas include deriving insights, defining meaningful metrics, solving business problems through data, and processing large datasets in a scalable manner. * Ideal candidates have owned analytical domains end-to-end, including: + Data modeling + Data quality + Experimentation analysis + Dashboarding + Monitoring + Stakeholder-facing analytics * Target profile: + Approximately 2/3 analytics, product thinking, and business problem-solving + Approximately 1/3 data engineering and data modeling * Candidates will be assessed on both technical data modeling skills and business orientation., * Ensure correctness, quality, and consistency of analytical datasets and logging. * Design and maintain scalable analytical data models and reusable data products. * Perform data governance responsibilities, including data classification, stewardship, quality monitoring, compliance, and security considerations. * Maintain and improve data pipeline health through monitoring, troubleshooting, performance tuning, and proactive risk mitigation. Analytics, Monitoring & Insights * Transform large and complex datasets into actionable insights for operational, historical, and predictive analysis. * Build reusable analytical datasets enabling self-service analytics across teams. * Develop application-specific monitoring tables, quality dashboards, and cost dashboards. * Analyze experiments, model behavior, and LLM evaluation results. * Validate data and GenAI products through exploratory analysis and visualizations before release. * Partner with product managers, scientists, and engineers to identify analytical opportunities and define analytics roadmaps. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)