AI/ML Engineer

Gartner seeks an experienced AI/ML Engineer to join our Data Intelligence Platform team. You will architect and implement advanced data solutions, support data operations, and enable data science innovation across our organization. This is a unique opportunity to work with an array of modern technologies, drive meaningful impact, and collaborate within a highly skilled, forward-thinking team., Architect, design, and implement scalable, high-performance data models and pipelines for analytics, reporting, and ML-driven applications

• Build and optimize robust SQL queries and in-application database operations from the ground up
• Integrate diverse data sources using REST APIs and harvesting tools, supporting both structured and unstructured data
• Automate deployment and management of data pipelines, applications, and AWS resources (EMR, ECS, Glue, Kinesis)
• Collaborate with business and data science stakeholders to gather requirements and deliver tailored solutions
• Champion best practices for data governance, access control, security, and performance optimization
• Partner with DevOps to enhance CI/CD processes, leveraging Terraform, Jenkins, and infrastructure-as-code
• Support database administration tasks: migration, backup, recovery, and cluster orchestration
• Continuously evaluate and integrate new cloud technologies to advance platform capabilities and efficiency

7-9 years of proven experience in cloud-based data model design, ETL pipeline development, and infrastructure for analytics and data science

• Expert-level proficiency in SQL and modern relational databases
• Hands-on skills with Spark, Glue, EMR, Apache Kafka/AWS Kinesis
• Strong programming background in Java, Python, Scala
• Experience with version control and automated build systems (Git, Jenkins)
• Deep knowledge of data structures, algorithms, and database engine configuration
• Familiarity with TDD/BDD practices and data governance principles
• Practical experience with AWS services and cloud deployments

Preferred Skills

• Experience deploying and maintaining ML models in production environments
• Proficiency with NoSQL, Graph, Document, Key-Value, and Time Series databases
• Exposure to advanced data security and compliance practices, Solution Design and Development of Cloud based data models ETL Pipelines and infrastructure for reporting analytics and data science.

Opportunity to work on cutting-edge data intelligence technologies shaping Gartner’s future

• Collaborative, high-performance team environment with ongoing learning and development
• Flexible contract role for experienced professionals seeking impactful projects