Job Description
Solution Architect : Data Engineering and Analytics

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 (GCP Focus):
- Extensive experience with GCP 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 GCP (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.

Requirements

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.

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