Data Architect Hands On Lead Data

Job Title: Data Architect (Hands-On Lead Data Engineer) Need - BFSI Experience

Employment Type: Full-Time

Location: Cary, NC

Work Model: Hybrid Onsite Tuesday through Thursday required from Day 1

Experience: 12 18 Years (Minimum 10 15+ years of relevant data engineering and architecture experience)

Role Overview

We are seeking a deeply technical, hands-on Data Architect / Lead Data Engineer to join Altimetrik in support of our premier insurance client, MetLife, in Cary, NC. This is a hybrid, hands-on engineering and architectural leadership role-not a purely managerial or coordination position. The ideal candidate will actively design, code, and deploy enterprise-scale Lakehouse platforms on Azure Databricks while leading the implementation of production Generative AI (LLM/RAG) and automated financial data reconciliation solutions.

• Enterprise Lakehouse Architecture: Design, architect, and implement scalable Bronze, Silver, and Gold Medallion architectures using Azure Databricks, Delta Lake, ADLS Gen2, and Azure Data Factory (ADF).

• Hands-On Data Engineering: Write, review, and optimize production-grade data pipelines using Python, PySpark, Scala, and SQL, focusing on metadata-driven ingestion frameworks, Spark performance tuning, and data quality.

• Production GenAI & LLM Solutions: Architect and deploy production-ready LLM and Retrieval-Augmented Generation (RAG) workflows-including embeddings, vector retrieval, prompt engineering, and enterprise Text-to-SQL or semantic layer solutions.

• AI-Driven Financial & Data Quality Automation: Build automated reconciliation, anomaly detection, and AI-driven data quality pipelines tailored to financial services, general ledger, and accounting datasets.

• Governance, Security & MLOps/LLMOps: Implement Unity Catalog, fine-grained access controls, PII data protection, and robust CI/CD pipelines (Azure DevOps, Terraform, Databricks Asset Bundles) alongside model evaluation and production AI monitoring.

• Technical Leadership: Provide architectural guidance, conduct code reviews, and mentor data engineering teams while remaining actively involved in daily production coding.

• Experience: 12 18 years of progressive experience in data engineering, enterprise data architecture, and distributed big data processing, with demonstrated recent hands-on production coding experience.

• Core Programming: Expert-level, production-grade proficiency in Python, PySpark, Scala, and SQL.

• Azure Data Ecosystem: Strong hands-on expertise in Azure Databricks (Delta Lake, Spark performance tuning, Jobs/Workflows, Unity Catalog), ADLS Gen2, and Azure Data Factory (ADF).

• Medallion & Pipeline Engineering: Proven track record implementing enterprise Lakehouse/Medallion architectures and metadata-driven ingestion frameworks at scale.

• Production Generative AI & LLMs: Hands-on experience designing and deploying production LLM/RAG solutions utilizing frameworks such as LangChain, LlamaIndex, or LangGraph, integrated with Azure OpenAI, OpenAI, or Databricks Model Serving.

• DevOps & Infrastructure as Code: Experience automating data and AI deployments using Azure DevOps (CI/CD), Terraform, and Databricks Asset Bundles.

• Data Security & Governance: Strong understanding of Azure security frameworks, data governance, PII protection, and role/attribute-based access controls.

• Domain Expertise: Prior experience in insurance or financial services, specifically working with general ledger (GL), accounting, or financial reconciliation data.

• Advanced AI & Semantic Architectures: Hands-on experience building knowledge graphs, ontologies, semantic layers, enterprise Text-to-SQL applications, and MLOps/LLMOps monitoring pipelines.