About this opportunity
DATAECONOMY Inc lists this AI/ML Data & ETL Data Architect opportunity in charlotte, North Carolina. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Charlotte, United States | Posted on 06/04/2026
DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
AI/ML Data & ETL Data Architect
Charlotte, NC
Full-time
Key Responsibilities
AI/ML Enablement & GenAI
Architect feature stores, training/inference pipelines, and MLOps workflows for insurance use cases fraud detection, claims triage, underwriting risk scoring, loss reserving, and customer churn/retention.
Design RAG and GenAI solution patterns for claims summarization, policy/document intelligence, and underwriter/agent copilots.
Establish model lifecycle controls: versioning, lineage, drift monitoring, evaluation, and human-in-the-loop review.
Define responsible-AI and governance guardrails appropriate to a regulated insurance environment (auditability, explainability, bias monitoring).
Own the end-to-end target-state architecture for the insurance data platform policy administration, claims, billing, underwriting, actuarial, and reinsurance domains across raw, curated, and analytics-ready layers.
Design lakehouse and AI/ML reference architectures (Bronze/Silver/Gold Medallion) that unify structured, semi-structured, and streaming insurance data.
Define data domain boundaries, source-to-target mappings, and canonical insurance data models for shared enterprise consumption.
Produce architecture diagrams, design decision records, and patterns that engineering teams can implement consistently.
Make build-vs-buy, cloud service selection, and cost/performance trade-off decisions and defend them to client architecture review boards.
Design scalable, production-grade ETL/ELT frameworks (PySpark, Spark SQL, Delta Live Tables / equivalent, orchestrated Workflows).
Define ingestion patterns for batch, micro-batch, and streaming insurance feeds (policy, claims, payments, third-party/bureau data).
Establish orchestration, monitoring, alerting, and automation standards for the engineering team.
Data Modeling
Design dimensional models (star/snowflake) and canonical/conformed models for analytical and actuarial workloads.
Apply normalization/denormalization strategies balancing performance, usability, and regulatory traceability.
Ensure data quality, integrity, and alignment with enterprise and insurance regulatory governance policies.
Governance, Security & Compliance
Embed PII/PHI handling, masking, tokenization, and least-privilege access models into platform design.
Align architecture with insurance regulatory and audit requirements (e.g., NAIC model standards, state DOI, HIPAA where health lines apply, SOC 2, GDPR/CCPA).
Define metadata management, data lineage, and cataloging strategy (Unity Catalog or equivalent).
Advanced hands-on data engineering: Spark, Delta Lake / lakehouse, Workflows, Unity Catalog (or cloud-native equivalents).
AI/ML tooling: MLflow or equivalent, feature stores, model serving, and GenAI/RAG frameworks (LangChain/LangGraph or similar).
Strong SQL and Python programming with performance tuning skills.
Cloud platform depth (AWS / Azure / GCP), including managed data and ML services.
Required Qualifications
Hands-on AI/ML pipeline and MLOps experience, including at least one production GenAI/RAG deployment.
Strong command of Medallion architecture (Bronze/Silver/Gold) and modern data modeling for warehousing and analytics.
Proficiency with PySpark, SQL, ETL/ELT frameworks, and Delta Lake (or equivalent) optimization.
Experience with CI/CD, Git, and job orchestration tooling.
Insurance, financial services, or other regulated-industry delivery experience.
Demonstrated ability to present and defend architecture to senior client and review-board stakeholders.
Preferred Skills
Data governance, metadata management, and Unity Catalog (or equivalent) advanced features.
Streaming technologies (Auto-Loader / Structured Streaming / Kafka / Event Hubs / Kinesis).
Data security, regulatory compliance, and fine-grained access models.
Cost optimization and performance tuning in cloud environments.
Tools such as Airflow, Databricks Workflows, dbt, or similar.
Requirements
Strong Python (PySpark) and SQL programming with performance tuning
Databricks (or equivalent) Spark, Delta Lake, Workflows, Unity Catalog
ETL/ELT framework design and data modeling (dimensional, star/snowflake, canonical)
AI/ML pipelines + MLOps, plus at least one production GenAI/RAG deployment
Cloud experience AWS, Azure, or GCP (managed data + ML services)
CI/CD, Git, job orchestration
12+ years total; 3+ years as architect/lead; regulated-industry delivery
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Worksite address
charlotte, NC, 28245, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.