Data Architect - (Data and AI Strategy Consultant)

Prodapt; Reading; On-site; GBP 80,000 - 120,000

Job description

Overview

As a Data and AI Strategy Consultant,

• you are responsible for helping Enterprise to be data driven and working closely with the data architecture leadership and IT leadership in developing and implementing data and AI strategies related to enterprise data management and ML, AI and analytics.
• you will guide organizations through the process of optimizing data management, data governance, analytics, and business intelligence, enabling them to unlock actionable insights that drive better business decisions.
• you will provide support in developing accelerators, support RFPs, and creating more market opportunities.
• you will contribute to the data and AI revenue of the company.
• you will represent the organisation in international conferences, summits, drive catalyst projects and establish peer connect in the industry.

Responsibilities

• Data Strategy Development:
  • Collaborate with senior leadership and stakeholders to understand business goals, challenges, and opportunities.
  • Develop data strategies that align with business priorities, ensuring the effective use of data assets across the organization.
  • Devise strategies for how the organisation can collect, store, manage, and utilize data effectively and prepare it for business consumption. This includes identifying key business objectives and determining how data can support those objectives.
  • Define key performance indicators (KPIs) and data requirements to support business objectives.
• Data Governance & Management:
  • Establish best practices, policies and procedures for ensuring the quality, security, and integrity of data across the organization.
  • Guide the implementation of data governance frameworks to ensure compliance, security, and accessibility. This may involve overseeing compliance with regulations such as GDPR and all other prevalent regulations.
  • Assist in building data management processes and data architectures that support scalability and efficiency.
• Technology Evaluation and Implementation:
  • Assess various data management technologies and tools to determine which ones best suit the organization's needs. They may also oversee the implementation of these technologies and ensure they integrate seamlessly with existing systems.
  • Provide recommendations for business intelligence tools, dashboards, and reporting solutions to drive data-driven decision-making.
  • Evaluate existing analytics practices and propose solutions for optimizing data analysis and reporting.
  • The person has to be conversant with technologies like Snowflake, AWS, Tableau, Erwin, Kafka and Striims and should be very well aware of their responsibilities.
• Data Transformation & Optimization:
  • Lead clients in transforming their data infrastructure to support advanced analytics, AI, and machine learning initiatives.
  • Recommend ways to optimize data storage, integration, and access to enhance performance and reduce costs.
  • Assist clients in migrating from legacy systems to modern, cloud-based data platforms.
• Collaboration and Communication:
  • Collaborate with cross-functional teams including IT, marketing, finance, and operations to understand their data needs and align data strategies with overall business objectives. Effective communication skills are crucial for presenting findings and recommendations to stakeholders at all levels of the organization.
  • Lead workshops, training sessions, and presentations to promote data literacy and encourage a data-driven culture.
  • Serve as a trusted advisor to executives and business leaders on data-driven initiatives.

Requirements

• Bachelor's or Master's degree in Data Science, Business Analytics, Computer Science, Information Systems, or a related field.
• At least 15+ years of experience in data strategy, consulting, or data management roles.
• Proven experience in developing and implementing data strategies for diverse industries.
• Strong understanding of data governance, data privacy regulations, and data security best practices.
• Expertise in data analysis, business intelligence tools (e.g., Power BI, Tableau), and analytics platforms.
• Solid understanding of data modeling, database management, and ETL processes.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies.
• Strong problem-solving skills and ability to translate complex data concepts into actionable insights.
• Excellent communication, presentation, and stakeholder management skills.
• Global travel to various customer locations and to support various customer engagements and relationships.
• Certifications (Preferred but not required):
  • Data Management or Business Intelligence certifications (e.g., CDMP, CBIP, Google Cloud Professional Data Engineer).
  • Relevant certifications in analytics, cloud platforms, or project management.