Katalyze AI Staff Data Engineer Position
Posted
Summary
Staff Data Engineer at Katalyze AI who owns data architecture standards and builds customer data integrations, scalable streaming infrastructure, and ETL/ELT pipelines supporting the company's biotech/pharma AI operations. Core tech includes Python, SQL, cloud data platforms, Flink, and Kinesis.
Join Katalyze AI as a Staff Data Engineer to lead in creating data architectures that empower our biotech innovations. Design integrations that streamline our AI processes.
In this essential role, you will be responsible for defining the data architecture and creating customer integrations pivotal for real-time data access. Your capability in building complex data streaming infrastructures and maintaining efficient data quality systems will significantly impact our operations in delivering accessible pharmaceuticals.
Key Responsibilities: • Own the architecture standards for data infrastructures • Build out data integration pipelines linking client systems • Develop scalable data streaming infrastructure with tools like Kinesis • Create and manage ETL/ELT pipelines for varying data types • Ensure data quality through observability frameworks
Requirements: • At least 7 years of data engineering experience • Proven expertise in choosing tools and making architecture decisions • Proficient in data streaming technologies like Flink • Strong skills in Python, SQL with cloud data platforms • Background in industrial data systems preferred
Empower Katalyze AI’s mission with your advanced data engineering expertise.
In this essential role, you will be responsible for defining the data architecture and creating customer integrations pivotal for real-time data access. Your capability in building complex data streaming infrastructures and maintaining efficient data quality systems will significantly impact our operations in delivering accessible pharmaceuticals.
Key Responsibilities: • Own the architecture standards for data infrastructures • Build out data integration pipelines linking client systems • Develop scalable data streaming infrastructure with tools like Kinesis • Create and manage ETL/ELT pipelines for varying data types • Ensure data quality through observability frameworks
Requirements: • At least 7 years of data engineering experience • Proven expertise in choosing tools and making architecture decisions • Proficient in data streaming technologies like Flink • Strong skills in Python, SQL with cloud data platforms • Background in industrial data systems preferred
Empower Katalyze AI’s mission with your advanced data engineering expertise.