SunnyData logo
SunnyData

With a strong Data Engineering backbone, we deliver Databricks projects from concept to production.

Solutions Architect – Platform, Cloud Infrastructure, Security

Solutions EngineerSolutions EngineerFull TimeRemoteLeadTeam 51-200H1B No SponsorCompany SiteLinkedIn

Location

Mexico

Posted

4 days ago

Salary

0

Seniority

Lead

Job Description

Solutions Architect – Platform, Cloud Infrastructure, Security

SunnyData

• 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.

Job 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: Cloud Security, Cloud Networking, Encryption, 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.
  • DevOps/DevSecOps: SDLC tooling such as Github, Gitlab, Continuous Inspection such as SonarQube and Artifact Management such as Artifactory
  • IaC tools like Terraform
  • 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.
  • 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.

Benefits

  • Innovative Environment: Work with cutting-edge technologies and industry leaders in data engineering and AI.
  • Customer Impact: Make a real difference in how businesses leverage data for strategic decision-making.
  • Career Growth: Opportunities for professional development and career advancement.
  • Collaborative Culture: Join a supportive team that values collaboration and knowledge sharing.

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