Databricks Architect

About the role

We are seeking an experienced Databricks Architect to help design, build, and optimize modern data platforms using the Databricks ecosystem. This role is ideal for someone who enjoys solving complex data challenges, architecting scalable cloud-based environments, and partnering directly with customers and stakeholders to deliver high-impact solutions.

The Databricks Architect will lead the design of Databricks environments, data pipelines, ETL frameworks, governance models, and quality control processes. Amivero’s team of IT professionals delivers digital services that elevate the federal government, whether national security or improved government services. Our human-centered, data-driven approach focuses on truly understanding the environment and the challenge, and reimagining with our customer how outcomes can be achieved. As a member of the Amivero team, you will use your empathy for a customer’s situation, your passion for service, your energy for solutioning, and your bias towards action to bring modernization to mission-critical, public-service government IT systems.

Special Requirements

• US Citizenship required to obtain Public Trust (DHS ICE Public Trust preferred)
• Master’s Degree + 9 years of relevant experience OR Bachelor’s Degree + 9 years of experience
• Experience architecting and securing API pipelines (Mulesoft, Kong) for optimal performance

Responsibilities

• Partner with customers, business stakeholders, data engineers, data scientists, and platform teams to understand requirements and translate them into technical solutions.
• Architect and design scalable, secure, and high-performing Databricks environments.
• Lead the development of modern ETL/ELT pipelines and data processing frameworks.
• Architect and configure virtual private cloud (VPC) instances within Databricks.
• Architect and secure API pipelines (Mulesoft, Kong) for optimal performance.
• Build and optimize data pipelines using Databricks capabilities, Spark, notebooks, workflows, and related cloud services.
• Architect effective, secure, and transparent model governance and data governance frameworks.
• Design and implement data governance, access control, and security models using Unity Catalog.
• Support the implementation and adoption of Unity Catalog AI Gateway and Agent Bricks capabilities.
• Establish data quality, validation, lineage, monitoring, and control processes.
• Provide architectural guidance, technical leadership, and best practices for Databricks-based data platforms.
• Evaluate existing data environments and recommend improvements for performance, scalability, reliability, and cost efficiency.
• Create solution documentation, architecture diagrams, design patterns, and implementation roadmaps.
• Serve as a trusted advisor in customer-facing conversations, workshops, and technical presentations.

Requirements

• Proven experience architecting and implementing Databricks environments.
• Strong background in data engineering, ETL/ELT design, and pipeline development.
• Experience architecting API pipelines (Mulesoft, Kong).
• Hands-on experience with Databricks, Apache Spark, Delta Lake, and cloud-based data platforms.
• Experience with Unity Catalog, including data governance, permissions, lineage, and access controls.
• Exposure to or experience with Unity Catalog AI Gateway and Agent Bricks.
• Strong understanding of data quality frameworks, data controls, validation, and monitoring.
• Experience designing scalable data architectures for batch and/or streaming workloads.
• Ability to work directly with customers and stakeholders in a consulting, advisory, or solution architecture capacity.
• Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
• Ability to lead architecture discussions, gather requirements, and recommend practical solutions.

Preferred Qualifications

• Experience with one or more major cloud platforms: AWS, Azure, or Google Cloud Platform.
• Experience with Lakehouse architecture and modern data platform design.
• Knowledge of machine learning, AI, GenAI, or MLOps concepts within Databricks.