Technical Architect/Sr. Technical Architect

Job Title:

Technical Architect/Sr.

Technical Architect Location:

Dallas, TX OR Chicago, IL Work Mode:

Hybrid Key Responsibilities Define the target architecture for the Lakehouse (TVHD), aligning with business and analytical needs. Design and implement Medallion architecture across Bronze, Silver, Gold, and ODS layers. Establish and enforce data modeling standards, schema design patterns, and data contracts. Define and implement data integration, ingestion, and transformation frameworks. Drive performance optimization strategies, including partitioning, caching, and Z-ordering. Ensure robust security, governance, lineage, and access control practices are embedded (e.g., RBAC, data masking, auditability). Review and approve technical designs, data pipelines, and coding standards. Guide engineering teams on best practices, scalability, reusability, and maintainability. Evaluate and mitigate technical risks, architecture gaps, and cross-platform dependencies. Partner with analytics and business stakeholders to enable data self-service and enterprise BI integration. Secondary Responsibilities Define and implement data quality and observability frameworks (e.g., validation rules, SLAs/SLOs, monitoring, alerting). Lead FinOps and cost optimization for data platforms (cluster policies, autoscaling, storage tiering, workload right-sizing). Oversee CI/CD and DevSecOps practices for data pipelines and Lakehouse assets (branching, automated testing, approvals). Plan and validate disaster recovery and high availability architectures, including backup and restore strategies. Coordinate security and compliance activities with InfoSec (policy alignment, audits, access reviews, lineage reporting). Drive platform modernization and migrations (e.g., Teradata to Lakehouse), including cutover planning and risk mitigation. Develop and maintain metadata standards and catalog taxonomy; promote data product thinking across domains. Support semantic modeling and self-service enablement for BI consumers (e.g., Power BI datasets, data contract enforcement). Conduct PoCs and technology evaluations to de-risk new capabilities (e.g., Unity Catalog features, streaming/CDC patterns). Establish reusable reference architectures, patterns, templates, and coding standards across teams. Mentor and upskill engineers; contribute to hiring, onboarding, and community of practice forums. Produce and maintain architecture documentation, runbooks, and knowledge-transfer materials. Partner with Enterprise/Solution Architects and Product/Program Managers on roadmaps, intake, and prioritization. Engage with vendors and procurement for tooling assessments, licensing, and support escalations. Support incident response and problem management for critical data platform issues; ensure root-cause analysis and remediation plans. Required Skills & Experience Minimum 15+ years across Data Warehousing, Data Engineering, and Analytics. Minimum 8+ years in cloud data architecture with at least 4+ years on Azure. Proven expertise in Cloud Data Architecture and Azure Databricks; hands-on with current technologies and end-to-end delivery. Strong proficiency with Databricks and Spark; deep experience on Azure (preferred). Experience with Teradata, SQL, and core data warehousing concepts. High proficiency building complex ETL/ELT data pipelines in Databricks using PySpark. Proven experience managing and maintaining Data Lake and Lakehouse environments, including CDC and SCD patterns. Experience with Unity Catalog (preferred) for centralized governance and access control. Experience integrating with Power BI and defining approaches for data self-service. Experience delivering progressive information management solutions and supporting the end-to-end SDLC. Ability to articulate clear objectives and define qualitative/quantitative measures of success. Extensive experience aligning application and analytics development with business outcomes. Exceptional analytical and problem-solving skills. Excellent communication and presentation skills; confident, methodical, and collaborative in a team environment. Preferred Attributes Track record of leading at least one large-scale, end-to-end data program in a Data Architect/Data Engineer capacity. Demonstrated ability to set and enforce engineering standards and reusable frameworks. Passion for continuous improvement in performance, cost optimization, and data quality.