Solutions Architect- Data Engineer and Analytics

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.