Solution Architect

Datascience

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1. Solution Design & Architecture:

Lead the architecture and design of scalable data solutions, including Big Data, Data Lake, and cloud implementations.

Design end-to-end data pipelines and architectures that support data ingestion, storage, processing, and access across distributed environments.

Ensure solutions are designed for high performance, availability, and reliability.

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2. Technical Leadership & Guidance:

Serve as a subject matter expert on data engineering and data architecture best practices.

Provide technical direction and guidance on cloud platforms (e.g., AWS, Azure, Google Cloud) and data technologies (e.g., Hadoop, Spark, Snowflake).

Guide the engineering teams in implementing best practices around data security, privacy, governance, and compliance.

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3. Stakeholder Collaboration:

Collaborate with business and analytics teams to understand data requirements and translate them into technical solutions.

Work closely with infrastructure, security, and DevOps teams to ensure seamless integration and secure deployment.

Act as a bridge between technical and non-technical stakeholders, ensuring clarity in requirements and solutions.

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4. Project Delivery & Execution:

Lead solution architecture and design sessions for data projects, driving requirements gathering, solution development, and delivery.

Ensure timely and efficient delivery of data solutions within budget and aligned with project goals.

Evaluate and select the appropriate technology stack and tools based on project needs and organizational standards.

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5. Continuous Improvement & Innovation:

Stay current with emerging technologies, trends, and best practices in Big Data, Data Lakes, and Cloud.

Continuously seek opportunities to improve existing systems and solutions, enhancing performance, scalability, and maintainability.

Propose and implement innovative approaches to optimize data storage, processing, and retrieval.

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Qualifications:

Bachelor s or Master s degree in Computer Science, Information Technology, or a related field.

Minimum 7 years of experience in data architecture and data solutions development, with a focus on Big Data, Data Lake, and cloud technologies.

Proven experience with major cloud platforms (AWS, Azure, Google Cloud) and associated data services.

Strong knowledge of data warehousing, ETL/ELT processes, data integration, and analytics frameworks.

Expertise in Big Data technologies (e.g., Hadoop, Spark, Kafka) and Cloudera platform and modern database technologies (e.g., NoSQL, SQL).

Solid understanding of data governance, security, and privacy best practices.

Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders.

Experience in Agile methodologies and DevOps practices is a plus.

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Preferred Certifications:

AWS Certified Solutions Architect, Google Professional Data Engineer, Microsoft Certified: Azure Solutions Architect, Cloudera certifications.

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Key Competencies:

Strategic Thinking

Problem-Solving

Project Management

Stakeholder Engagement

Technical Leadership

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Employment Type: Full-time

Location: [Specify Location or Remote Availability]

This role is ideal for a solution architect who is passionate about data and enjoys solving complex challenges by designing and implementing innovative data solutions.