Solutions Architect – Platform, Cloud Infrastructure, Security

Responsibilities

• Customer Engagement: Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions. In this role you will split your time evenly between billable and pre-sales activity.
• Technical Leadership: Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives.
• Pre-Sales Support: Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings.
• Project Oversight: Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes.
• Solution Design: Architect data solutions, incorporating best practices in data governance, security, and quality.
• Data Analysis: Evaluate data sources for their value, recommending data inclusion strategies to enhance analytical processes.
• Cross-Functional Collaboration and Leadership: Lead internal teams, provide direction and mentorship to project teams to deliver solutions and educate end users on data products and analytic environments.
• Problem Resolution: Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections.
• Quality Assurance: Test data movement, transformation code, and data components to ensure accuracy and reliability.

Requirements

• 7+ years as a hands‑on Solutions Architect with experience in Data Security or related areas. Expertise in two or more of the following: Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter‑Service Authentication, Secure Application Frameworks, Detection & Response
• Infrastructure and Security: designing data platforms on cloud infrastructure and services (AWS, Azure, or GCP), using best practices in cloud security and networking.
• Technical Proficiency: Expertise in Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Databricks platform, cloud platforms, security, automation, networking, or identity management
• Architecture and leadership skills: In‑depth understanding of the end‑to‑end data analytics workflow (e.g., data modeling, ETL processes, and data integration) using modern data engineering techniques; Ability to lead complex architecture requirements (discovery), solution design sessions and build out implementation architecture blueprints that can be implemented by data‑engineering and analytics teams.
• Programming Skills: Proficiency in Python, Java, or Scala
• Cloud Platforms: AWS, Azure, and/or GCP.
• SQL Expertise: Ability to write, debug, and optimize SQL queries.
• IaC tools like Terraform
• Client‑Facing Skills: Strong written and verbal communication skills with experience in client‑facing roles.
• Presentation Skills: Ability to create and deliver detailed presentations to clients and stakeholders.
• Documentation: Experience in creating detailed solution documentation including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views.
• Team Leadership: Experience leading teams and mentoring other engineers.
• End‑to‑End Solutions: Ability to develop end‑to‑end technical solutions into production, ensuring performance, security, scalability, and robust data integration.