This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Databricks Architect based in Brazil.
This is a senior technical role focused on designing and delivering modern, scalable data platforms using Databricks and Apache Spark.
You will lead end-to-end data engineering initiatives, including complex migrations from legacy platforms to modern Lakehouse architectures.
The role combines hands-on architecture, performance optimization, cloud engineering, and technical problem-solving across production environments.
You will collaborate closely with clients and technical teams to translate business and data requirements into robust solutions.
The position also offers exposure to emerging technologies across Generative AI, RAG, Databricks Genie, and modern data applications.
You’ll join a remote-first environment that values technical expertise, ownership, collaboration, and continuous learning.
This is an opportunity to influence high-impact data modernization projects while expanding your expertise across the Databricks ecosystem.
Accountabilities
- Design and implement enterprise-grade data solutions using Databricks, ensuring scalability, reliability, maintainability, and performance.
- Lead end-to-end Databricks initiatives, including architecture, development, implementation, and migrations from legacy data platforms.
- Design, develop, and optimize data processing solutions using Apache Spark, applying advanced techniques for performance and scalability.
- Partner with clients and Databricks Professional Services teams to define technical requirements, architecture approaches, and implementation strategies.
- Establish and maintain CI/CD practices and use Databricks Asset Bundles (DABs) to support reliable and repeatable deployments.
- Troubleshoot complex data platform and engineering challenges, identifying root causes and delivering scalable, high-quality solutions.
- Contribute to Data Engineering, Lakehouse, and data platform modernization initiatives across diverse projects and use cases.
- Apply Databricks performance-tuning techniques to optimize workloads, resource utilization, and overall platform efficiency.
- Stay current with emerging capabilities across the Databricks ecosystem and identify opportunities to incorporate technologies such as GenAI, RAG, Databricks Genie, and Databricks Apps.
- Collaborate effectively with distributed technical teams and stakeholders while providing technical guidance throughout project delivery.
Requirements
- 10+ years of total professional experience, with at least 7 years in Data Engineering, Data Platforms, Analytics, or closely related disciplines.
- Proven experience delivering 4–6+ end-to-end Databricks projects successfully into production environments.
- Databricks certification is mandatory, with Associate certification as the minimum requirement and Professional certification strongly preferred.
- Deep hands-on expertise with Apache Spark, including Spark internals, window functions, aggregations, clustering, and performance optimization.
- Demonstrated experience migrating data platforms and workloads from legacy technologies to Databricks.
- Strong expertise in at least one major cloud platform: AWS, Azure, or GCP.
- Practical experience implementing CI/CD pipelines and working with Databricks Asset Bundles (DABs).
- Strong understanding of Databricks architecture, Lakehouse concepts, scalability, and performance tuning.
- Knowledge of Generative AI, RAG, Databricks Genie, or Databricks Apps is a valuable advantage.
- Strong analytical and troubleshooting skills, with the ability to solve complex technical challenges independently.
- Excellent English communication skills and availability to work with US time-zone overlap.
- A collaborative mindset, strong ownership, and the ability to communicate technical concepts clearly with clients and engineering teams.
Benefits
- Remote-first culture with the flexibility to work from anywhere.
- Full coverage for AWS, DBT, Google Cloud, Azure, and Databricks certifications.
- Access to company-sponsored English lessons to support professional development.
- Birthday day off plus an additional vacation week.
- Referral bonuses for helping grow the team.
- Monthly credits through Maslow to use within a benefits marketplace.
- An annual team trip designed to strengthen collaboration and company culture.
- Monthly childcare reimbursement to support employees and their families.
- Opportunity to work on modern Data Engineering, Lakehouse, Machine Learning, and AI projects.
- Exposure to multiple cloud and data technologies while working in a distributed, collaborative environment.
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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