Data Engineer, AVS Digital Transformation; AI & Analytics

Job Description Summary

The GEHC Advanced Visualization Solutions (AVS) segment, a fast-growing business in GE Health Care, is the global leader in ultrasound medical devices and solutions. The portfolio spans the continuum of care to enable customers with ultrasound screening, diagnosis, treatment and monitoring of diseases. Our customers are seeking to improve efficiency in radiology and beyond and increase user confidence to provide better clinical outcomes continues to grow.

Consequently, the need for AI, digital solutions, and automation, connecting devices and software in one seamless ecosystem continues to proliferate.

This person will design and build comprehensive data solutions that will power GE Healthcare’s AVS segment’s next generation of analytics and AI. In this hands-on role, you will design and build curated semantic layers, scalable pipelines, and enterprise-grade sematic models –whilst layering in AI-powered capabilities using approved platforms as the foundation matures.

No sponsorship or OPT for this role

Job Description

* No sponsorship or OPT for this role

As the Data Engineer of the AVS Digital Transformation team, you’ll bridge enterprise data strategy with segment-specific innovation to deliver self-service analytics, conversational AI, predictive insights and intelligent automation within AVS.

• Design and implement curated, semantic data layers (dimensional models, business definitions), ensuring accuracy, traceability, and AI/ML readiness for BI and generative AI use cases.

• Design scalable SQL-based pipelines to transform raw and enterprise data into analytics-ready assets

• Implement data quality frameworks, lineage, and governance, according to standards set by the central data office team.

• Lead enterprise-grade Power BI semantic model design (Dataflows, composite models, aggregations) to enable low-latency, high-performance reporting for executives and analysts.

• Integrate and extend enterprise semantic models with AVS-specific business logic and conformed dimensions, aligning definitions across the segment.

• Define best practices for DAX, M, and workspace governance (deployment pipelines, refresh strategies) within team to advance BI maturity and self-service

• Partner with visualization analysts and business leaders to translate requirements into trusted, performant models and reusable domain data products.

• Design AI-ready semantic layers and metadata that enable natural-language querying, conversational analytics, automated retrieval and intelligent workflows

• Build and deploy AI solutions using enterprise-approved platforms. Implement operational forecasting, anomaly detection and segmentation.

• Engage central AI/ IT for evaluation, architecture guidance and enterprise deployment of AI use cases that exceed approved platform capabilities

• 8+ years in data architecture/engineering delivering dimensional models, curated marts, and production pipelines in cloud environments (e.g., AWS Redshift/S3/Glue, Microsoft Fabric/Azure, ADF or equivalent).

• Mastery of SQL, DAX, and Power Query (M); strong performance tuning and model optimization at scale.

• Deep Power BI experience: semantic modeling, composite models, aggregations, dataflows, and Fabric integration.

• Hands‑on with Copilot Studio, Fabric Data Agents, or AWS Bedrock.

• Familiarity with Power Apps / Power Automate for end‑to‑end digital workflows.

• Microsoft certifications: DP‑600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), PL‑300 (Power BI Data Analyst), AZ-900 (Azure AI), PL-400 (Power Platform Developer Associate)

• AI/ML integration:
  Python for data prep/modeling; designing data/semantics for NLQ, agentic systems, and platforms such as AWS Bedrock or Fabric ML.

• Experience partnering with centralized AI and data teams to produce models and agentic solutions.

• ERP/CRM data integration (e.g., Oracle EBS, Salesforce) and familiarity with enterprise data governance.

We will not sponsor individuals for employment visas, now or in the future, for this job opening.

For U.S.…