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Solution Architect, Data Analytics

$ 8,000 - $ 12,000 / month

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Key Responsibilities: * Solution Design & Architecture:
  • Lead the end-to-end architecture design of data analytics platforms, including data ingestion, storage, processing, and visualization layers.
  • Develop scalable and high-performance solutions for real-time and batch data processing.
  • Define architecture standards, guidelines, and best practices for analytics solutions.
  • Stakeholder Collaboration:
  • Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
  • Act as the technical liaison between business teams, data engineers, and developers to ensure alignment and clarity.
  • Technology Leadership:
  • Evaluate emerging data analytics tools, frameworks, and technologies to incorporate into the organization's technology stack.
  • Provide technical expertise in areas such as cloud-based data platforms, big data solutions, and AI/ML integration.
  • Project Management:
  • Guide cross-functional teams in the successful implementation of data analytics projects within agreed timelines and budgets.
  • Ensure all solutions are secure, compliant, and aligned with regulatory requirements.
  • Optimization & Innovation:
  • Drive innovation by identifying opportunities to enhance analytics capabilities and improve data workflows.
  • Optimize existing systems for performance, cost-efficiency, and reliability.
Requirements:
Education and Experience:
  • Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.
  • Minimum of 8 years of experience in solution architecture with a focus on data analytics, data engineering, or related fields.
  • Proven experience in designing and implementing data analytics solutions for large-scale enterprises.
Technical Skills:
  • Expertise in cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and their analytics services.
  • Proficiency in big data technologies such as Hadoop, Spark, Kafka, or similar tools.
  • Excellent understanding of ETL/ELT processes, data warehousing (e.g., Snowflake, Redshift, BigQuery), and database technologies (SQL/NoSQL).
  • Experience with BI tools like Tableau, Power BI, or Looker.
  • Familiarity with AI/ML frameworks and integrating advanced analytics into solutions.
Soft Skills:
  • Excellent communication and presentation skills to interact effectively with technical and non-technical stakeholders.
  • Excellent problem-solving skills with a strategic mindset.
  • Leadership and mentoring experience in guiding technical teams.