Databricks Solution Architect in United States at Jobgether
NewJob Function: Design
Jobgether
United States, United States
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Job Description
Databricks Solution Architect
Accountabilities:
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Databricks Solution Architect based in the United States.
This role is a senior technical leadership position responsible for designing and scaling a modern cloud-based data lakehouse platform built on Databricks. You will define the end-to-end architecture that powers large-scale analytics, machine learning, and data engineering across enterprise environments. The position plays a critical role in shaping how data is ingested, transformed, governed, and optimized across petabyte-scale systems. You will work closely with data scientists, analytics teams, and business stakeholders to turn complex requirements into scalable technical solutions. This is a hands-on architecture role combining deep engineering expertise with strategic platform ownership. You will also mentor engineers, establish technical standards, and influence best practices across the data organization. The environment is highly collaborative, cloud-native, and focused on delivering scalable, production-grade data systems.
- Architect and lead the design and implementation of an enterprise Databricks-based lakehouse platform using technologies such as Delta Lake, Unity Catalog, Photon, and Databricks Workflows.
- Design and build scalable batch and streaming data pipelines using PySpark, Spark SQL, Structured Streaming, and Delta Live Tables across multiple data sources.
- Define and enforce data platform standards including medallion architecture, CI/CD practices, testing frameworks, observability, and cost optimization strategies.
- Lead data governance implementation using Unity Catalog, including access control, lineage tracking, auditability, and secure handling of sensitive data.
- Optimize Spark workloads for performance and cost efficiency through tuning strategies such as partitioning, autoscaling, Z-ordering, caching, and cluster optimization.
- Partner with data science and ML teams to operationalize machine learning models using MLflow, feature stores, and model serving capabilities.
- Own cloud infrastructure architecture including networking, IAM, storage, encryption, and Infrastructure-as-Code using Terraform.
- Mentor and guide data engineering teams through architecture reviews, code reviews, and engineering best practices.
- Collaborate with business, analytics, and product stakeholders to translate requirements into a scalable data platform roadmap.
- Ensure compliance with information security and data protection standards across the data lifecycle (e.g., GDPR, CCPA).
- 8+ years of experience in data engineering, including at least 4+ years working extensively with Databricks in production environments.
- Deep expertise in Apache Spark (PySpark and Spark SQL), including performance tuning, execution optimization, and distributed processing concepts.
- Strong hands-on experience with Databricks ecosystem tools such as Delta Lake, Unity Catalog, Delta Live Tables, and Databricks Workflows.
- Proven experience deploying cloud-based data solutions on AWS, Azure, or GCP, including IAM, networking, and storage services.
- Proficiency in Python and SQL; Scala experience is a plus.
- Strong understanding of medallion architecture and dimensional data modeling for analytics use cases.
- Experience implementing CI/CD pipelines and DevOps practices using Git, Terraform, and data deployment frameworks.
- Demonstrated ability to lead technical initiatives end-to-end and mentor engineering teams in complex environments.
- Excellent communication skills with the ability to align technical and non-technical stakeholders.
- Strong problem-solving mindset with the ability to operate in large-scale, high-performance data environments.
- Annual salary range of $102,000 – $133,000, depending on experience and qualifications.
- Fully remote work flexibility within the United States.
- Opportunity to lead architecture for large-scale, enterprise-grade Databricks data platforms.
- Exposure to advanced cloud, data engineering, and machine learning technologies.
- Leadership responsibilities including mentoring and shaping engineering standards.
- Visa sponsorship available for eligible candidates.
- Inclusive, collaborative, and innovation-driven work environment.
- Strong focus on professional development and continuous learning.
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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Job Location
United States, United States
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