Enterprise Architect – Data, Cloud & AI

Hi, Hope You are doing well. This is Piyush from Tanisha Systems. I have a job opportunity for you, if you are interested, please share your Resume and details ASAP. Enterprise Architect – Data, Cloud & AI

Location:

Scottsdale, AZ / San Francisco, CA – Onsite Hire Type:
Contract-to-Hire (CTH) Must-Have Skills Databricks | Cloudera | Snowflake | Data Engineering

Role Overview We are seeking a highly experienced Enterprise Architect to define and drive enterprise technology strategy across Data Platforms, Cloud, AI/ML, Analytics, and Enterprise Integration. The ideal candidate will have strong hands-on architecture experience with Databricks, Cloudera, Snowflake, Hadoop, Data Engineering, and Cloud Platforms, along with the ability to design scalable, secure, resilient, and future-ready enterprise solutions. This role will work closely with executive leadership, business stakeholders, engineering teams, architects, and customers to define enterprise architecture, establish technology standards, drive modernization, and deliver large-scale digital, data, and AI transformation initiatives.

Key Responsibilities Enterprise Architecture & Technology Strategy Define enterprise-wide architecture standards, reference architectures, technology principles, and strategic technology roadmaps. Lead architecture governance, solution reviews, technology evaluations, and architecture decision processes. Design scalable, resilient, secure, highly available, and cost-optimized enterprise platforms. Align enterprise technology architecture with business objectives, digital transformation strategies, and long-term organizational goals. Drive cloud adoption, legacy modernization, platform engineering, and enterprise transformation initiatives.

Evaluate emerging technologies and recommend solutions that provide measurable business and operational value. Data Platform Architecture Architect enterprise-scale data platforms using Databricks, Cloudera, Snowflake, Hadoop, and cloud-native data services. Design and implement modern Lakehouse, Data Warehouse, Data Lake, Data Mesh, and Data Fabric architectures. Define enterprise data governance, metadata management, data lineage, security, and access-control frameworks. Establish standards for data quality, observability, monitoring, compliance, and operational reliability.

Develop strategies for managing structured, semi-structured, and unstructured enterprise data. Define scalable data architecture patterns supporting analytics, AI/ML, reporting, and business intelligence. Data Engineering & ETL Architecture Architect large-scale ETL/ELT frameworks supporting batch, streaming, and real-time data processing. Lead the architecture of scalable data pipelines integrating multiple enterprise source systems. Define data integration and processing patterns using Apache Spark, PySpark, Databricks, Cloudera/Hadoop, Kafka, and cloud-native services.

Establish best practices for data ingestion, transformation, orchestration, processing, and delivery. Optimize data pipelines for performance, scalability, reliability, and cost efficiency. Provide architectural guidance to data engineering teams on modern data processing and integration patterns. Cloud Architecture Design enterprise solutions across AWS, Microsoft Azure, and Google Cloud Platform (GCP). Lead cloud migration, modernization, and hybrid/multi-cloud architecture initiatives. Architect highly available, secure, scalable, and resilient cloud platforms.

Define Infrastructure as Code (IaC), CI/CD, Dev Ops, and platform engineering strategies. Establish cloud governance standards covering security, networking, identity, monitoring, compliance, and cost management. Promote Fin Ops and cloud cost-optimization practices…