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Service Health and Quality: Maintain the health and quality of services and incidents, proactively identifying and resolving issues. Utilize service health indicators and telemetry for action providing recommendations to optimize performance. Conduct thorough root cause analysis and drive the implementation of measures to prevent future recurrences. Dev Ops Model: Understanding of working in a DevOps Model. Taking ownership from working with product management on requirements to design, develop, test, deploy and maintain the software in production. 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Performing source code management and thorough testing to ensure that analytics solutions provided are consistent with the quality and requirements of the business. Position requires either: (i) a Bachelor's degree (or an equivalent foreign degree) in Computer Science, Software Engineering, IT or a closely related field and 5 years of experience as a Business Intelligence or Data Engineer or (ii) a Master's degree (or an equivalent foreign degree) in Computer Science, Software Engineering, IT or a closely related field and 3 years of experience as a Business Intelligence or Data Engineer. 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BI-Specific Technical & Execution Expertise: 8+ years of progressive experience in software engineering, with at least 3+ years in a leadership role managing teams focused on Business Intelligence, data warehousing, or data analytics Extensive hands-on experience leading the design, development, and deployment of complex, large-scale enterprise BI solutions, including data modeling, ETL/ELT processes, data warehousing, and advanced data visualization Deep understanding of data governance, data quality, and data security principles and experience implementing them within BI solutions. Experience with modern BI platforms and visualization tools (e.g., Power BI, Tableau, Looker, Qlik, Sisense, or similar) and the underlying data architectures that support them Proficiency with cloud-based data warehousing solutions (e.g., Snowflake, BigQuery, Redshift) and experience building BI applications on cloud platforms (e.g., AWS, Azure, GCP) Solid understanding of integrating internal or external enterprise systems via APIs, events, or other integration implementations to source data for BI purposes. Familiarity with containerization technologies (e.g., Docker, Kubernetes) in the context of deploying BI components or data pipelines Team Leadership & Development: Proven experience attracting, hiring, mentoring, retaining, and leading high-performance teams of BI engineers and data professionals (i.e., FTEs, not contractors) in a fast-paced, dynamic product development environment. Ability to foster a culture of innovation, collaboration, and continuous improvement within the BI engineering team. Operational Excellence & Delivery: Experience driving agile development methodologies and best practices for BI development lifecycles, ensuring timely and high-quality delivery. Strong project management skills with a track record of successfully delivering complex BI projects on time and within budget. Excellent communication and stakeholder management skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences, including customers and executive leadership. Provide technical mentorship and guidance to engineers at all levels, fostering a culture of learning, collaboration, and continuous improvement. Manage team workload and capacity, setting priorities and managing risks and tradeoffs. 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Proven experience in building Cohort of Excellence and Community of Practice across geographies for process automations, and AI practice. Keen understating of Ethical AI principles, laws and regulations. Experience building process excellence outcome frameworks and leading cross-functional AI teams, including product managers, analysts, data scientists, and AI/ML/GenAI/Deep Learning developers. Experience with AI strategies and leading enterprise-wide transformation initiatives, deployment of AI platforms and collaboration with vendors, industry partners and academic researchers. Strong understanding of AI, GenAI, Machine Learning, Deep Learning, Agents, and Automation technologies (Copilots, AWS, Azure OpenAI, RAG, MCP, GPT , UIPath), and the ability to manage both people and process side of change effectively using structured methodology such as (PROCI, Lean, Six sigma, CRISP-DM, Malcolm Baldridge Excellence Framework, Rainbow Framework, NIST AI600-1) Ability to think strategically and develop long-term plans for AI, Agents and Automation initiatives. Proactive senior executive collaboration and hands on training skills. Excellent verbal and written communication skills, with the ability to present complex technical concepts to non-technical stakeholders. 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