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Key facts
Job Title

Freelance - Data Analytics Engineer

Role type

Contract

Start date

ASAP

Remote friendly

Yes

Location

Amsterdam, North Holland, Netherlands

Salary

€70 - €100 per hour €

Short version:
- Data Analaytics engineeer
- Freelance registered is a must
- GenAI experience
- Hands on experience with Python and Pyspark
- Experience working with relational databases in analytical environments.
- Work extensively with free text, unstructured data, LLM-generated outputs, and AI application telemetry.
Data Analytics Engineer II - GenAI Application Teams
This role sits within a fast-growing GenAI application environment supporting search and discovery, AI companions and chatbots, customer support AI, and LLM evaluation workflows. The team focuses on turning complex, large-scale data into actionable insights that directly impact AI-driven products.
As a Data Analytics Engineer II, you will own analytical data domains end-to-end and work closely with product managers, engineers, and scientists. The role is highly business-oriented and centered on application logic, analytics, experimentation, data modeling, and insight generation rather than platform or infrastructure ownership.
Responsibilities
  • You will own business and application data domains from ingestion to consumption, ensuring correctness, quality, and consistency of analytical datasets and logging. You will design and maintain scalable analytical data models and reusable data products while taking responsibility for data governance, classification, quality monitoring, compliance, and security.
  • You will monitor and improve data pipeline health through proactive troubleshooting, performance tuning, and risk mitigation. You will transform complex datasets into insights for operational, historical, and predictive analysis, enabling self-serve analytics across teams.
  • You will build application-specific monitoring tables, quality dashboards, and cost dashboards. A key part of the role is analyzing experiments, model behavior, and LLM evaluation results, validating GenAI products through exploratory analysis and visualization prior to release, and contributing to analytics roadmaps together with product and engineering stakeholders.
Required Skills and Experience
  • You bring at least 3 years of experience in analytics, data, or software-adjacent roles working with large-scale data. You have strong SQL skills, hands-on experience with Python and PySpark, and solid knowledge of data modeling and modern data warehouse practices.
  • You are comfortable working with unstructured and free-text data, including LLM-generated outputs and AI telemetry. Experience in ML or AI product environments, evaluation workflows, or model error analysis is a strong advantage.
  • You communicate clearly with both technical and non-technical stakeholders, work independently in ambiguous environments, and are proactive in owning problems end-to-end. Experience with dbt, Snowflake, Streamlit, Airflow, or Argo is considered a plus.

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