What are the responsibilities and job description for the Artificial Intelligence Data Architect position at Landbase?
About Us
At Landbase, we harness the expertise of over 100 world-class sales professionals and AI to deliver targeted, high-quality leads on autopilot. Our mission is to achieve GTM automation, freeing humans from software-related tasks so they can reclaim their day. We're building GTM-1 Omni, a pioneering action model designed for lead generation.
The Role
We seek an exceptional Data Engineer to design and implement scalable data pipelines that power our AI models and analytics. This individual will be responsible for crafting ETL pipelines in PySpark and/or Scala Spark, orchestrating complex data workflows in Airflow, and developing advanced SQL skills with BigQuery. The ideal candidate will have hands-on experience with MongoDB, Elasticsearch, and PostgreSQL, as well as proficiency in GCP Dataproc and cluster optimization. They will also handle TB-scale unstructured data, optimize database performance and storage strategies, create and maintain data quality monitoring systems, collaborate with ML Engineers on production model deployment, and stay current with emerging AI tools and technologies.
Requirements
At Landbase, we harness the expertise of over 100 world-class sales professionals and AI to deliver targeted, high-quality leads on autopilot. Our mission is to achieve GTM automation, freeing humans from software-related tasks so they can reclaim their day. We're building GTM-1 Omni, a pioneering action model designed for lead generation.
The Role
We seek an exceptional Data Engineer to design and implement scalable data pipelines that power our AI models and analytics. This individual will be responsible for crafting ETL pipelines in PySpark and/or Scala Spark, orchestrating complex data workflows in Airflow, and developing advanced SQL skills with BigQuery. The ideal candidate will have hands-on experience with MongoDB, Elasticsearch, and PostgreSQL, as well as proficiency in GCP Dataproc and cluster optimization. They will also handle TB-scale unstructured data, optimize database performance and storage strategies, create and maintain data quality monitoring systems, collaborate with ML Engineers on production model deployment, and stay current with emerging AI tools and technologies.
Requirements
- Design and implement ETL pipelines in PySpark and/or Scala Spark
- Orchestrate complex data workflows in Airflow
- Advanced SQL skills and experience with BigQuery
- Hands-on experience with MongoDB, Elasticsearch, and PostgreSQL
- Proficiency with GCP Dataproc and cluster optimization
- Experience handling TB-scale unstructured data
- Optimize database performance and storage strategies
- Create and maintain data quality monitoring systems
- Collaborate with ML Engineers on production model deployment
- Stay current with emerging AI tools and technologies
- 3 years of experience in large scale data engineering
