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Delivery Lead
1 month ago
Desired candidate should have - Bachelor's or Master's degree in Computer Science, Data Analytics, Information Systems, or a related field is preferred. - Minimum of 15 years managing large-scale data and analytics projects, with a focus on platform modernization and transformation. - Strong knowledge of modern data warehousing solutions, cloud platforms (e.g., AWS, Azure, GCP), and big data technologies. - Excellent understanding of data concepts, data modelling methods and experience in data management capabilities including data definitions, data quality management and data integration. - Proven leadership in managing multi-disciplinary teams across various phases of complex data projects. - Familiarity with data science workflows, machine learning integration, and AI tools to drive value and efficiency. - Exceptional analytical skills with a proactive approach to problem-solving and innovation. - Excellent verbal and written communication skills to effectively engage with technical and non-technical stakeholders. - Personally invested in continuous improvement and innovation. - Motivated, self-directed individual that works well with minimal supervision. Role : - Oversee and drive the successful delivery of the multi-year data modernization program, ensuring alignment with strategic business goals and timelines. - Lead the migration of existing data assets to the enterprise data platform assuring cutting edge architecture, modern, scalable, and future-ready platform. - Utilize Agile practices to manage and deliver outcomes effectively, adapting to changes in scope, priorities, and technology in a dynamic environment. - Manage the development and integration of data warehouse, reporting tools, and advanced data science components to meet evolving business needs. - Identify and implement opportunities for process improvements, automation, and optimization through advanced data science methodologies. - Collaborate with business leaders, technical teams, and external partners to ensure seamless communication and alignment throughout the project lifecycle. - Champion the adoption of AI-backed capabilities to enhance data analysis, predictive modeling, and actionable insights. - Proactively identify potential delivery risks and develop mitigation strategies to keep the program on track. - Establish and monitor key performance indicators (KPIs) to measure the effectiveness and impact of the data solutions delivered. - Lead efforts to continuously evaluate and data strategies and methodologies in line with the evolving needs of the business, ensuring our capabilities remain cutting-edge and aligned with both current and future goals. - Re-evaluate and refine methods and strategies as needed, taking into account the current and future business needs, as well as the evolving technology landscape during this period of Transformation. - Stay on the forefront of emerging technologies and best practices, continuously evaluating new opportunities for their potential to drive business value and enhance our AI offerings - Work closely with business teams, sponsors, and internal stakeholders to ensure alignment of scope and requirements, fostering the achievement of transformation objectives. - Operate effectively within an environment with global reach, understanding the broad business impacts of decisions and actions across various functions. (ref:hirist.tech)
