Technical Architect (BIBA)

Key Responsibilities

• Define the target architecture for the Lakehouse, 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.