Senior Data Architect in United States Embassy at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Architect based in United States.

This role offers the opportunity to design and deliver advanced cloud-based data solutions that help organizations unlock the value of their information assets. As a Senior Data Architect, you will shape modern data platforms, including Lakehouse and data warehouse architectures, while supporting AI and analytics initiatives. You will collaborate with business stakeholders, engineering teams, and clients to transform complex data challenges into scalable technical solutions. The position combines hands-on architecture, cloud engineering expertise, consulting, and technical leadership. You will contribute to data governance, quality, automation, and best practices across enterprise environments. This is an ideal opportunity for a data professional who enjoys solving complex problems, mentoring teams, and driving innovation through modern cloud technologies.

The Senior Data Architect will lead the design, development, and implementation of scalable cloud data architectures while providing technical guidance to delivery teams and clients. This role requires strong expertise in data engineering, cloud platforms, governance, and modern analytics solutions to deliver reliable and high-performing data ecosystems.

• Lead the architecture, design, and implementation of Lakehouse and data warehouse solutions within cloud-based environments.
• Translate business requirements into technical data strategies and scalable architecture designs.
• Collaborate with stakeholders to understand data needs and develop solutions aligned with business objectives.
• Establish and implement data governance frameworks, policies, and procedures to improve data management practices.
• Ensure data quality, integrity, security, and compliance through effective validation and monitoring processes.
• Design reusable, scalable data components and frameworks to support future analytics and AI initiatives.
• Lead and mentor data engineering teams, providing technical direction and architectural guidance.
• Develop cloud data solutions using platforms such as Azure, AWS, and GCP while following industry best practices.
• Troubleshoot, optimize, and maintain cloud data environments to improve performance, reliability, and scalability.
• Guide teams on emerging data, analytics, and AI/ML technologies while supporting adoption of modern solutions.
• Partner with delivery and support teams to improve automation, deployment processes, and operational efficiency.
• Support professional services engagements by advising clients on data architecture strategy and implementation.
• Present technical recommendations, project outcomes, and architecture decisions to clients and internal teams.
• Lead the orchestration and automation of cloud-based data platforms.

The ideal candidate is an experienced data architecture professional with a strong background in cloud platforms, distributed data systems, and enterprise analytics solutions. They should have consulting experience, strong technical expertise, and the ability to communicate effectively with both technical and business audiences.

• Bachelor’s degree in computer science, engineering, data-related fields, or equivalent professional experience.
• 7+ years of experience in data architecture, data engineering, analytics, performance optimization, pipeline integration, and infrastructure configuration.
• 10+ years of consulting experience delivering technology solutions for clients.
• Strong experience designing and implementing cloud data platforms using Azure, AWS, or GCP.
• Deep expertise in at least one major cloud ecosystem and working knowledge of additional cloud platforms.
• Advanced understanding of Lakehouse architecture, data warehouse design, data modeling, and modern data management practices.
• Hands-on experience with Databricks, Spark, Delta Lake, Iceberg, Hudi, and distributed computing environments.
• Strong knowledge of Spark Structured Streaming, Spark performance optimization, and cluster configuration.
• Experience designing and managing data pipelines using technologies such as Databricks Delta Live Tables and DBT.
• Understanding of MLOps concepts and experience supporting AI/ML model development and deployment workflows.
• Experience with Terraform, Git, CI/CD pipelines, automation, and integration testing.
• Knowledge of data governance, security models, Unity Catalog, access controls, and enterprise data management.
• Familiarity with Databricks APIs, SCIM APIs, CLI tools, testing processes, and deployment workflows.
• Experience implementing data quality controls, ingestion patterns, CDC, CDF, and Slowly Changing Dimensions (SCD Type 1/Type 2).
• Strong problem-solving skills with the ability to identify and resolve complex technical challenges.
• Excellent communication, leadership, and client-facing presentation skills.
• Ability to travel up to 15% as required.

Preferred qualifications include:

• Databricks Data Engineering Professional or Associate certification.
• Cloud certification in Azure, AWS, or GCP.
• Experience building enterprise-scale AI and analytics platforms.
• Familiarity with advanced data security and governance frameworks.

• Remote work flexibility within the United States.
• Competitive compensation package based on experience and qualifications.
• Opportunity to work on innovative cloud, data, and AI transformation projects.
• Exposure to diverse industries and complex enterprise technology environments.
• Career growth opportunities through technical leadership and consulting engagements.
• Collaborative environment with experienced cloud, data, and engineering professionals.
• Opportunity to influence modern data architecture strategies and best practices.
• Travel opportunities for client collaboration and project delivery.