Solution Architect : Data Engineering and Analytics

Location: San Francisco, CA (onsite work)
Full-time direct hire

Technical Expertise

• Data Architecture & Design:
  • Proven experience designing scalable, secure, and performant data architectures for big data and analytics workloads.
  • Expertise in data modeling techniques (dimensional, entity-relationship, etc.)
  • Knowledge of data governance frameworks and data quality best practices.
• Cloud Platform Proficiency (Google Cloud Platform Focus):
  • Extensive experience with Google Cloud Platform services for data engineering and analytics (BigQuery, Dataflow, Dataproc, Pub/Sub, etc.).
  • Ability to design and implement cloud architecture for data processing and analytics at scale.
  • Understanding of cloud security best practices and compliance requirements.
• Data Engineering & Integration:
  • Strong understanding of data pipelines, ETL/ELT processes, and data transformation techniques.
  • Proficiency in programming languages like Python, Java, or Scala.
  • Experience with data orchestration tools (Airflow, Luigi) and containerization technologies (Docker, Kubernetes).
• Programming and Scripting:
  • Strong skills in programming languages like Python, Java, or Scala.
  • Ability to write, analyze, and debug SQL queries.
• Data Analytics and Visualization:
  • Working knowledge of data analysis tools and platforms.
  • Proficiency in data visualization tools and techniques to present data insights effectively.
• Machine Learning and AI (Optional):
  • Knowledge of machine learning algorithms and their application in data analytics.
  • Familiarity with AI and ML services on Google Cloud Platform (AI Platform, AutoML, etc.).

Analytical Skills

• Data Strategy and Business Intelligence:
  • Ability to develop strategies for data collection, analysis, and dissemination.
  • Experience in delivering business intelligence and data-driven insights to stakeholders.
• Problem-Solving and Performance Optimization:
  • Strong analytical and problem-solving skills to address complex data-related issues.
  • Experience in optimizing data workflows, queries, and algorithms for performance and cost-efficiency.

Managerial and Soft Skills

• Project Management:
  • Experience in leading and managing large-scale data projects.
  • Familiarity with project management tools and methodologies (e.g., Agile, Scrum).
• Communication and Leadership:
  • Excellent communication skills to articulate technical concepts to non-technical stakeholders.
  • Leadership skills to guide and mentor teams.
• Collaboration and Teamwork:
  • Ability to work collaboratively with cross-functional teams.
  • Experience in working in a global, multi-cultural environment.
• Continuous Learning and Adaptation:
  • Commitment to continuous learning and staying updated with the latest trends in technology, data engineering, and analytics.
  • Ability to adapt to evolving business and technology landscapes.

Additional Considerations (Optional):

• Experience with data visualization tools (Tableau, Power BI).
• Familiarity with data security and privacy regulations (GDPR, HIPAA).
• Experience in a specific industry vertical relevant to your organization.