About The Role

Lead the design of end-to-end data platform solutions, ensuring they meet both business and technical requirements.
Architect scalable, high-performance data platforms leveraging technologies such as cloud-based solutions (AWS, Azure, GCP), data lakes, data warehouses, ETL/ELT pipelines, and real-time data streaming.
Design integrated solutions that can handle diverse data sources (structured, semi-structured, unstructured) and support advanced analytics, machine learning, and AI applications.

Define the long-term vision and roadmap for the data platform, ensuring alignment with the organization’s data strategy and business goals.
Develop migration and modernization strategies for legacy data systems to modern data platforms, including cloud adoption and hybrid architectures.
Evaluate emerging technologies and industry trends to recommend innovative solutions that enhance the data platform’s capabilities.

Collaborate closely with data engineers, data scientists, business analysts, and other IT teams to ensure that data architectures align with business objectives and deliver the necessary insights for decision-making.
Work with business stakeholders to understand data requirements, translating them into technical specifications and ensuring solutions meet business needs.
Foster collaboration across technical teams to ensure the seamless integration of systems, data sources, and workflows.

Implement data governance frameworks, ensuring that data is accurate, consistent, and accessible across the organization while maintaining the highest levels of security and compliance.
Develop and enforce data security policies, ensuring that data is protected in compliance with regulatory standards such as GDPR, CCPA, HIPAA, etc.
Establish data lineage and metadata management practices to support data integrity and transparency.

Lead the design and implementation of cloud-based data solutions, optimizing data storage, compute, and analytics services to ensure performance, scalability, and cost-efficiency.
Drive cloud migration projects, working with engineering teams to move on-premises data solutions to cloud platforms (Azure, AWS, GCP).
Architect solutions for data warehousing, data lakes, and analytics, ensuring that the architecture is resilient, flexible, and cost-optimized.

Ensure that the data platform is capable of handling large volumes of data and providing low-latency access for real-time analytics and reporting.
Continuously assess and optimize the performance, scalability, and cost-efficiency of the data architecture.
Lead the design of systems that scale efficiently, both vertically and horizontally, to accommodate growing data needs.

Provide technical leadership to the data engineering and architecture teams, ensuring best practices and high standards are maintained in solution design and implementation.
Mentor junior team members, offering guidance on architectural design, data modelling, and the latest data technologies.
Promote a culture of continuous learning, encouraging team members to stay up to date with industry trends and innovations.

Oversee the implementation and delivery of data platform solutions, ensuring they are deployed successfully and meet technical specifications.
Troubleshoot and resolve any issues related to the data architecture and platform.
Ensure solutions are delivered on time and within budget, meeting both functional and non-functional requirements.

Create and maintain comprehensive documentation for data architecture, solution designs, and technical processes.
Produce regular status reports and updates to senior management, highlighting key milestones, risks, and opportunities.

Bachelor’s or master’s degree in computer science, Engineering, Information Technology, or a related field.
Minimum of 7+ years of experience in data architecture, data engineering, or a similar role, with a strong focus on designing large-scale data platforms.
Proven experience in architecting cloud-based data solutions, including data lakes, data warehouses, ETL pipelines, and analytics platforms (Azure, AWS, GCP).
Strong knowledge of data modelling, data governance, data security, and cloud-native data technologies.
Experience with data integration techniques, including ETL/ELT processes, real-time data streaming, and batch processing.
Expertise in big data tools (e.g., Hadoop, Spark), database systems (e.g., SQL, NoSQL), and data warehousing platforms.
Strong understanding of data privacy, security, and compliance frameworks (e.g., GDPR, HIPAA).
Experience in leading data migration projects and modernizing legacy data systems.

Strong leadership, collaboration, and communication skills.
Expertise in cloud platforms and services (Azure preferred).
Proficiency in data pipeline orchestration tools (e.g., Apache Airflow, Azure Data Factory).
Knowledge of containerization and microservices architecture.
Familiarity with data visualization and BI tools (e.g., Power BI, Tableau).
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
Ability to think strategically while balancing business needs and technical solutions.
Experience with Agile methodologies and working in a fast-paced, collaborative environment.

Certifications such as Microsoft Certified: Azure Solutions Architect Expert or Google Cloud Professional Data Engineer .
Experience with machine learning and AI workloads on data platforms.
Knowledge of DevOps practices and CI/CD for data pipelines.

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