Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.
About the role
- Senior Developer working on data cycle from tracking to analytics for NIO, a tech company transforming lives with connectivity. Collaboration with product, marketing, and leadership teams.
Responsibilities
- Define, document and validate events, metrics and KPIs.
- Structure conversion, behavior and retention funnels.
- Translate business objectives into measurable metrics.
- Support areas such as Product, Marketing, Engineering and Leadership.
- Ensure data quality, consistency and governance.
- Design and implement data projects from inception to delivery.
- Implement complete tracking for apps and digital platforms.
- Define and validate events in Google Analytics 4 (GA4).
- Model and organize data in Google BigQuery.
- Develop analytical and executive dashboards in Looker Studio.
- Create analytical datasets prepared for scale and evolution.
- Support the delivery of insights for management and leadership.
Requirements
- Advanced SQL (BigQuery, PostgreSQL, MySQL, CTEs, Window Functions, optimization).
- Python for analysis (Pandas, NumPy, detailed EDA, report automation).
- BI & Visualization (Looker Studio, Power BI, Tableau).
- Web & App Analytics (Google Analytics 4 - GA4).
- Business metrics (conversion, retention, churn, CAC, LTV, ROI).
- Data storytelling and clear communication of results.
- Data ingestion and integration via REST APIs, GA4, Firebase and relational databases. Construction of ETL/ELT pipelines.
- Organizing data in raw, trusted and analytics layers.
- Data transformations using SQL and Python.
- Orchestration with Apache Airflow (DAGs, automation and monitoring).
- Distributed processing with Apache Spark / PySpark.
- Basic concepts of streaming and real-time processing with Apache Kafka.
- Data modeling (Fact/Dimension, Data Marts, KPI-oriented models).
- Version control with Git / GitHub.
- Applied classical machine learning (regression, classification, trees, Random Forest, XGBoost, clustering - K-Means, DBSCAN).
- Applied statistics (hypothesis testing, correlation, basic inference).
- Time series and forecasting (trends and seasonality, Statsmodels / Prophet).
- Hands-on experience with LLMs and generative AI (ChatGPT, Claude, Gemini, prompt engineering, automation of analyses and reports).
- Concepts of RAG (Retrieval-Augmented Generation) and MLOps (pipelines, versioning and basic monitoring).
- Behavioral profile: clear and objective communication. Strong analytical skills and critical thinking. Autonomy with technical responsibility. Collaborative and results-oriented. Continuous interest in technical growth and learning.
Benefits
- Meal and/or food allowance
- Transportation voucher
- Health insurance
- Dental insurance
- Life insurance
- Private pension plan
- Profit-sharing program (PPR)
- Pharmacy assistance
- Childcare assistance
- Flexible working hours
- V.tal benefits club
- Extended maternity leave (6 months)
- Extended paternity leave (20 days)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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