Enterprise Architect

Job Description

Job Description

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

We are seeking a highly experienced Enterprise Architect to define and drive the enterprise technology strategy across Data Platforms, Cloud, AI/ML, Analytics, and Enterprise Integration. The ideal candidate will be responsible for designing scalable, secure, and future-ready architectures leveraging Databricks, Snowflake, Hadoop, Cloud Platforms (AWS/Azure/GCP), APIs, Data Engineering, Automation, and AI/ML technologies. The architect will collaborate with executive leadership, business stakeholders, engineering teams, and customers to build enterprise-scale digital, data, and AI solutions that maximize business value and operational efficiency.

• Enterprise Architecture & Strategy
  • Define enterprise-wide architecture standards, reference architectures, and technology roadmaps.
  • Lead architecture governance, solution reviews, and technology selection decisions.
  • Design scalable, resilient, secure, and cost-optimized enterprise platforms.
  • Align technology architecture with business objectives and digital transformation initiatives.
  • Drive cloud adoption, modernization, and platform engineering programs.
• Data Platform Architecture
  • Architect enterprise data platforms using Databricks, Snowflake, Hadoop, and cloud-native services.
  • Design modern Lakehouse, Data Warehouse, and Data Mesh architectures.
  • Define enterprise data governance, metadata management, lineage, and security frameworks.
  • Establish data quality, observability, monitoring, and compliance standards.
  • Design structured and unstructured data management strategies.
• Data Engineering & ETL
  • Architect large-scale ETL/ELT frameworks for batch and real-time processing.
  • Lead the design of scalable data pipelines across multiple source systems.
  • Define data integration patterns using Spark, Databricks, Hadoop ecosystem, and cloud-native services.
  • Establish best practices for ingestion, transformation, orchestration, and data delivery.
  • Optimize performance and scalability of enterprise data pipelines.
• Cloud Architecture
  • Design enterprise solutions across AWS, Azure, and GCP.
  • Drive cloud migration and modernization initiatives.
  • Architect highly available, secure, and scalable cloud platforms.
  • Define Infrastructure as Code (IaC), CI/CD, and DevOps strategies.
  • Ensure cloud governance, security, networking, and FinOps best practices.
• AI/ML & Advanced Analytics
  • Define enterprise AI/ML architecture strategy.
  • Architect MLOps frameworks and model lifecycle management.
  • Design Generative AI, Agentic AI, RAG, and LLM integration architectures.
  • Establish AI governance, monitoring, security, and responsible AI practices.
  • Enable business intelligence, predictive analytics, and advanced AI capabilities.
• API & Integration Architecture
  • Define enterprise integration architecture and API strategy.
  • Design microservices, event-driven, and API-first architectures.
  • Establish integration patterns using REST APIs, GraphQL, messaging systems, and streaming frameworks.
  • Ensure secure, scalable, and reusable enterprise integrations.
• Quality Engineering & Test Automation
  • Define enterprise testing strategy for data, cloud, APIs, and applications.
  • Architect automated testing frameworks for ETL, Data Quality, API, AI/ML, and cloud platforms.
  • Drive adoption of CI/CD-integrated quality engineering practices.
  • Establish reliability, observability, and performance testing standards.
• Leadership & Stakeholder Management
  • Act as trusted advisor to business and technology leadership.
  • Mentor architects, engineers, and technical leads.
  • Lead architecture reviews and technical governance forums.
  • Drive innovation and adoption of emerging technologies.

• Data Platforms
  • Databricks Lakehouse
  • Snowflake
  • Hadoop Ecosystem (HDFS, Hive, Spark, YARN)
  • Data Warehouse & Data Lake Platforms
  • Delta Lake
  • Data Mesh & Data Fabric
• Data Engineering
  • ETL / ELT Architecture
  • Data Pipelines
  • Apache Spark
  • PySpark
  • Kafka
  • Streaming & Real-Time Processing
  • Data Quality & Observability
• Cloud Platforms
  • AWS
  • Microsoft Azure
  • Google Cloud Platform (GCP)
  • Cloud Security & Networking
  • Infrastructure as Code (Terraform, CloudFormation)
• AI/ML
  • Machine Learning Platforms
  • MLOps
  • Generative AI
  • Large Language Models (LLMs)
  • Agentic AI
  • RAG Architectures
  • Vector Databases
• API & Integration
  • REST APIs
  • GraphQL
  • Enterprise Service Bus (ESB)
  • Event-Driven Architecture
  • Microservices
• Automation & DevOps
  • CI/CD Pipelines
  • GitHub/GitLab
  • Jenkins
  • Docker
  • Kubernetes
  • Test Automation Frameworks
• Database Technologies
  • Snowflake
  • SQL Server
  • PostgreSQL
  • Oracle
  • NoSQL Databases

• Executive stakeholder management
• Strategic thinking
• Architectural leadership
• Strong communication and presentation skills
• Problem-solving and decision-making
• Customer engagement and consulting experience

This role is ideal for organizations looking to build and modernize enterprise-scale Data, AI, Cloud, and Digital platforms while driving innovation, governance, and business transformation.