Job Description
This role focuses on the data and machine learning infrastructure behind our clients internal pricing and inventory decision-support tool. The emphasis is on scalable pipelines, model serving, and monitoring infrastructure that ensure the tool delivers fresh, reliable data and stable predictions during live operations to be used by used by venue operators and site managers.
Day to day, the Data Engineer / AI Engineer will:
Build and maintain batch and near real-time data pipelines for POS, inventory, telemetry, and vendor feeds.
Normalize and integrate data from multiple vendors into a unified analytics and ML foundation.
Develop APIs and services to serve model outputs (pricing recommendations, demand forecasts, financial impact).
Operationalize ML models with versioning, deployment workflows, and rollout controls.
Implement monitoring and moderation for data quality and model behavior at scale.
Integrate outputs with dashboards, alerts, and internal business tools used by site managers.
Produce well-documented, maintainable engineering code and architecture artifacts.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:
Skills and Requirements
Strong experience as a Data Engineer or AI/ML Engineer in production environments.
Proven experience with:
Batch and streaming data pipelines
Model deployment and serving (APIs, microservices, inference workflows)
Monitoring, logging, and observability for ML systems
Experience working with IoT or telemetry data.
Cloud-native background; Snowflake experience preferred.
Comfortable operating in multi-vendor data ecosystems.
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