Solution Architect, Data Analytics

Key Responsibilities:

1. 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.

1. 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.

1. 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.

1. 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.

1. 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.