Data Architect (15-20 yrs)
Location: Remote
About the Role:
We are hiring on behalf of one of our clients - a boutique consulting firm specializing in Data and AI - for an experienced Databricks Architect. The ideal candidate will lead the design and delivery of scalable data platforms and AI-driven solutions within the Databricks ecosystem.
This is a senior technical role that requires strong architectural expertise, leadership skills, and a passion for building data-driven systems that enable real business impact.
Key Responsibilities:
- Solution Architecture: Design and implement scalable, secure, and high-performing Databricks-based solutions aligned with client needs.
- Data Engineering: Architect and build end-to-end data pipelines, data lakes, and data warehouse solutions using Databricks.
- Analytics & ML Enablement: Collaborate with data scientists and analysts to design and deploy ML and analytics workloads on Databricks.
- Performance Optimization: Ensure cluster performance, cost efficiency, and resource utilization are continuously optimized.
- Security & Governance: Implement data governance frameworks, security controls, and compliance standards within Databricks.
- Client Engagement: Partner with client stakeholders to translate business goals into technical architecture and delivery plans.
- Thought Leadership: Stay current with Databricks innovations and industry best practices, guiding teams on their adoption and implementation.
Requirements:
- Total Experience: 13-20 years overall experience in data engineering and analytics, with at least 5+ years working on Databricks.
Technical Expertise:
- Strong hands-on experience with Apache Spark, Delta Lake, and Databricks APIs.
- Proficiency in Python, Scala, or Java.
- Proven experience in ETL design, data warehousing, and data governance.
- Leadership: Experience leading technical teams, mentoring engineers, and driving architecture decisions.
- Communication: Excellent interpersonal and client-facing communication skills.
Good to Have:
- Certifications: Databricks Certified Professional or equivalent credentials.
- Cloud Experience: Exposure to AWS, Azure, or GCP.
- Machine Learning: Understanding of ML concepts and familiarity with common ML frameworks and libraries.
- If you're a seasoned data professional passionate about Databricks architecture and want to make a measurable impact through modern data platforms, we'd love to connect with you.
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