Data & ai engineer
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Summary
Designs and maintains scalable data pipelines, ingestion, and tokenization on Google Cloud Platform using BigQuery, Airflow, and Python, while integrating LLMs into production with prompt engineering and agentic workflows. Looker experience is a plus.
Role Overview We are seeking a highly skilled Data & AI Engineer with extensive GCP experience to join our team.
¿Es este el puesto que está buscando? Si es así, siga leyendo para obtener más detalles y no olvide enviar su solicitud hoy mismo.
In this role, you will be responsible for building robust data pipelines, managing data ingestion and tokenization, and leveraging cutting-edge AI technologies to drive business solutions.
The ideal candidate will bridge the gap between traditional data engineering and advanced generative AI implementation.
Key Responsibilities Design, build, and maintain scalable data pipelines and ingestion processes.
Implement data tokenization strategies to ensure data security and compliance.
Develop and optimize workflows using Apache Airflow.
Integrate LLMs into production environments, including designing and optimizing agentic workflows.
Apply prompt engineering techniques to improve model performance and reliability.
Collaborate with cross-functional teams to deliver high-quality data solutions.
Qualifications Technical Skills: Strong expertise in Google Cloud Platform (GCP).
Proficiency in Big Query and general Data Engineering practices.
Experience with Data Ingestion and Data Tokenization.
Strong programming skills in Python.
Hands-on experience with Apache Airflow. xqbhyrx
AI/ML Expertise: Proven experience with LLMs, prompt engineering, agentic workflows, and deploying AI models into production.
Preferred Skills: Experience with Looker is highly preferred but not mandatory
¿Es este el puesto que está buscando? Si es así, siga leyendo para obtener más detalles y no olvide enviar su solicitud hoy mismo.
In this role, you will be responsible for building robust data pipelines, managing data ingestion and tokenization, and leveraging cutting-edge AI technologies to drive business solutions.
The ideal candidate will bridge the gap between traditional data engineering and advanced generative AI implementation.
Key Responsibilities Design, build, and maintain scalable data pipelines and ingestion processes.
Implement data tokenization strategies to ensure data security and compliance.
Develop and optimize workflows using Apache Airflow.
Integrate LLMs into production environments, including designing and optimizing agentic workflows.
Apply prompt engineering techniques to improve model performance and reliability.
Collaborate with cross-functional teams to deliver high-quality data solutions.
Qualifications Technical Skills: Strong expertise in Google Cloud Platform (GCP).
Proficiency in Big Query and general Data Engineering practices.
Experience with Data Ingestion and Data Tokenization.
Strong programming skills in Python.
Hands-on experience with Apache Airflow. xqbhyrx
AI/ML Expertise: Proven experience with LLMs, prompt engineering, agentic workflows, and deploying AI models into production.
Preferred Skills: Experience with Looker is highly preferred but not mandatory