The DataOps Engineer will oversee the Lakehouse environment, managing incidents, monitoring data pipelines, conducting root cause analysis, and ensuring data quality and operational integrity.

Lead as a Data Architect to design and enforce Lakehouse architectures, establish data modeling standards, and mentor engineers while collaborating with stakeholders to deliver AI solutions.

Lead architect for AWS Lakehouse architecture; responsible for platform health, scalability, disaster recovery, and self-service tooling. Manage AWS Glue jobs, Apache Iceberg tables, and deploy governance tools for data quality. Collaborate with teams to optimize operations and drive adoption of automated solutions.

As a Generative AI Engineer, you will design, build, and maintain AI systems leveraging Large Language Models and implement robust MLOps practices.

As a Data Assurance Lead, you will implement a Data Assurance Framework, automate data contracts, and ensure data quality in complex Lakehouse environments, particularly for financial services clients.

The Data Modeler will design and implement scalable data models in Lakehouse architectures, focusing on semantic layers, knowledge graphs, and collaboration with data teams.

The AI Platform Engineer designs and manages on-premises AI infrastructure, optimizes ML workloads, and collaborates on high-performance computing environments while ensuring security and reliability.

The AWS Glue Data Engineer will migrate source systems to the Lakehouse, build and optimize ingestion pipelines, and ensure data quality and compliance, collaborating closely with various teams.

The Data Engineer designs and optimizes scalable data solutions, manages data pipelines, and implements MLOps principles to support AI systems and enhance data quality and governance.

Lead the design and delivery of an AI-powered text-to-SQL platform while managing a team to integrate AI solutions with existing BI systems in a fast-paced environment.