Databricks Resident Solution Architect [Remote]

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

As a Databricks Resident Solution Architect, you will provide senior technical leadership for modern cloud data platforms built on the Databricks Lakehouse.
You will shape architecture, governance, security, and platform strategies within complex enterprise environments.
The role combines hands-on data engineering expertise with architectural leadership and stakeholder engagement.
You will guide teams across data engineering, analytics, and AI/ML initiatives while translating business objectives into scalable technical solutions.
A strong focus on Unity Catalog, Lakehouse architecture, performance, security, and cost optimization will be central to your work.
You’ll operate as a trusted technical authority, mentoring engineering teams and driving consistent architectural standards.
This is an opportunity to influence long-term enterprise data strategies while remaining deeply involved in implementation and platform adoption.

Accountabilities

• Architect and guide the implementation of modern Databricks data platforms using Lakehouse and Medallion architecture principles.

• Provide hands-on technical leadership across data engineering, analytics, and AI-enabled use cases within the Databricks ecosystem.

• Establish and enforce enterprise data governance, security, access controls, and data management standards using Databricks Unity Catalog.

• Enable AI and machine learning workloads, including ML pipelines and model lifecycle integration across the platform.

• Optimize platform performance, scalability, reliability, and cost efficiency using a FinOps-oriented approach.

• Collaborate with business leaders, architects, engineers, and other stakeholders to align platform capabilities with enterprise data and analytics objectives.

• Act as a resident technical authority, providing architectural guidance, mentoring engineering teams, and ensuring solution quality and consistency.

• Support the development of long-term platform strategies and help organizations adopt scalable, governed, and AI-ready data capabilities.

Requirements

• 10+ years of overall experience in data engineering, data architecture, analytics engineering, or closely related disciplines.

• 5+ years of hands-on experience with Databricks, including Delta Lake, Unity Catalog, Workflows/Jobs, and Lakehouse architecture.

• Mandatory Databricks Professional Certification.

• Strong expertise in Apache Spark, preferably PySpark, along with advanced Python and SQL capabilities.

• Proven experience designing and implementing production-grade, large-scale data pipelines and enterprise data platforms.

• Hands-on experience with at least one major cloud platform, with Azure preferred; AWS or GCP experience is also acceptable.

• Strong knowledge of data modeling, Medallion architecture, governance, and enterprise data platform design.

• Familiarity with CI/CD pipelines, infrastructure automation technologies such as Terraform, and Agile delivery practices.

• Excellent communication and stakeholder-management skills, with the ability to operate effectively in complex or regulated enterprise environments.

• Strong architectural judgment, problem-solving capabilities, mentoring skills, and the ability to translate business requirements into practical technical solutions.

Benefits

• Fully remote opportunity within the United States.

• Senior architectural ownership across modern Databricks and Lakehouse environments.

• Opportunity to influence enterprise data strategy, governance, analytics, and AI/ML adoption.

• Hands-on exposure to leading cloud technologies, data engineering practices, and platform architecture.

• Opportunity to work directly with business and technical stakeholders in complex enterprise environments.

• Leadership and mentoring opportunities across data engineering and analytics teams.

• Compensation and additional benefits are subject to the partner company's employment terms and applicable policies.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.