Dataiku Specialist
⚲ Warszawa, Gdańsk, Olsztyn, Białystok, Szczecin, Łódź, Poznań, Kraków, Wrocław, Lublin
20 160 - 23 520 PLN netto (B2B)
Wymagania
- Machine Learning
- AWS
- Git
- CI/CD
- Dataiku
- Azure
- GCP
- SQL
- Python
Opis stanowiska
We are looking for a Dataiku Specialist to join our team and act as the primary expert for our Dataiku DSS (Data Science Studio) platform. In this role, you will be responsible for designing end-to-end data pipelines, implementing machine learning models, and empowering both technical and non-technical stakeholders to leverage AI effectively. You will play a key role in scaling our data science efforts by ensuring projects are governed, reproducible, and ready for production.
Key Responsibilities
•
Pipeline Development: Design and build automated data preparation and ETL workflows using Dataiku’s visual recipes and custom code (Python/SQL).
• ML & Analytics: Develop, train, and deploy machine learning models within the Dataiku environment.
• Platform Governance: Manage and optimize Dataiku projects, ensuring best practices for version control, documentation, and resource management.
• Operationalization (MLOps): Transition lab-stage experiments into robust production scenarios using Dataiku Automation and API nodes.
• Collaboration: Act as a bridge between Data Scientists, Data Engineers, and Business Analysts to democratize data usage across the organization.
• Optimization: Monitor flow performance and troubleshoot execution bottlenecks within the DSS platform.
Required Skills & Experience
• Dataiku Expertise: Proven experience working with Dataiku DSS (visual recipes, plugins, lab, and automation nodes).
• Data Engineering: Strong proficiency in SQL and Python for data manipulation and custom coding.
• ML Knowledge: Solid understanding of the machine learning lifecycle (feature engineering, model evaluation, and deployment).
• Cloud & Architecture: Familiarity with cloud platforms (AWS, Azure, or GCP) and how Dataiku integrates with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery).
• Collaboration Tools: Experience with Git integration and CI/CD concepts within the Dataiku ecosystem.
• Soft Skills: Ability to translate business problems into technical "flows" and mentor other users on the platform.
Key Responsibilities
•
Pipeline Development: Design and build automated data preparation and ETL workflows using Dataiku’s visual recipes and custom code (Python/SQL).
• ML & Analytics: Develop, train, and deploy machine learning models within the Dataiku environment.
• Platform Governance: Manage and optimize Dataiku projects, ensuring best practices for version control, documentation, and resource management.
• Operationalization (MLOps): Transition lab-stage experiments into robust production scenarios using Dataiku Automation and API nodes.
• Collaboration: Act as a bridge between Data Scientists, Data Engineers, and Business Analysts to democratize data usage across the organization.
• Optimization: Monitor flow performance and troubleshoot execution bottlenecks within the DSS platform.
Required Skills & Experience
• Dataiku Expertise: Proven experience working with Dataiku DSS (visual recipes, plugins, lab, and automation nodes).
• Data Engineering: Strong proficiency in SQL and Python for data manipulation and custom coding.
• ML Knowledge: Solid understanding of the machine learning lifecycle (feature engineering, model evaluation, and deployment).
• Cloud & Architecture: Familiarity with cloud platforms (AWS, Azure, or GCP) and how Dataiku integrates with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery).
• Collaboration Tools: Experience with Git integration and CI/CD concepts within the Dataiku ecosystem.
• Soft Skills: Ability to translate business problems into technical "flows" and mentor other users on the platform.
🔍 Dekoder Ogłoszenia
🔴
empowering both technical and non-technical stakeholders to leverage AI effectively
Oczekuje się, że będziesz szkolić i wspierać osoby bez technicznego zaplecza w korzystaniu z narzędzi AI, co może oznaczać dużo pracy edukacyjnej i tłumaczenia.
🔴
play a key role in scaling our data science efforts
Może to oznaczać, że firma dopiero zaczyna rozwijać swoje możliwości w zakresie Data Science i będziesz musiał budować wiele procesów od podstaw.
🟡
ensure projects are governed, reproducible, and ready for production
Wymaga to wdrożenia i utrzymania rygorystycznych standardów zarządzania projektami i kodem, co może być czasochłonne.
🟡
Act as a bridge between Data Scientists, Data Engineers, and Business Analysts to democratize data usage across the organization
Będziesz musiał komunikować się z różnymi grupami, co może wymagać umiejętności mediacji i tłumaczenia złożonych koncepcji na zrozumiały język.
🔴
troubleshoot execution bottlenecks within the DSS platform
Może to oznaczać, że platforma Dataiku jest już mocno obciążona lub ma ograniczenia, które będziesz musiał rozwiązywać.