Role: Senior Business Consultant - Data Management Location: San Francisco, CA Responsibilities: 1. Data Strategy Development: * Lead the development and execution of the organization's data strategy, aligning data initiatives with overall business goals and objectives. * Define long-term data strategies, including data collection, management, analysis, and usage, ensuring alignment with corporate priorities. * Identify key opportunities to leverage data as a strategic asset across the business. * Develop and maintain a roadmap for data initiatives that integrates various departments' needs (e.g., marketing, finance, operations, etc.). 2. Data Governance and Quality Management: * Establish and enforce data governance frameworks to ensure data quality, consistency, and compliance across the organization. * Define best practices for data collection, storage, access, and utilization to ensure data integrity. * Work with IT, data engineering, and other teams to ensure data privacy and security standards are followed, meeting compliance requirements (e.g., GDPR, CCPA). * Oversee the implementation of data management policies and procedures that promote transparency, trust, and accountability in the organization's data usage. 3. Collaboration with Business Leaders: * Serve as the primary point of contact for all data-related initiatives across business functions. * Work with business stakeholders to understand their data needs, translate those into actionable data strategies, and ensure data solutions are aligned with business objectives. * Translate complex data issues into clear, actionable insights for non-technical stakeholders, enabling informed decision-making at all levels of the organization. * Work closely with leadership teams to ensure data strategies support long-term business growth and innovation. 4. Data Analytics and Insights: * Provide guidance on data analytics best practices and methodologies, enabling teams to extract actionable insights from data. * Ensure that business teams are utilizing data effectively for operational, tactical, and strategic decision-making. * Champion data-driven decision-making across the organization by identifying key performance indicators (KPIs) and metrics that align with business priorities. * Leverage advanced analytics, including predictive models and data visualizations, to help guide business decisions and strategies. 5. Data Infrastructure and Tools: * Collaborate with data engineering and IT teams to ensure that the organization has the right tools, platforms, and technologies for collecting, analyzing, and visualizing data. * Identify gaps in data infrastructure and recommend improvements or new technologies to enhance data capabilities. * Stay up-to-date on the latest advancements in data analytics tools and technologies, and drive the adoption of relevant tools to improve data workflows. 6. Performance Monitoring and Reporting: * Track and monitor the effectiveness of data strategies, ensuring data initiatives deliver measurable business value. * Design and implement reporting systems and dashboards to track key business metrics and performance indicators. * Provide regular reports to executive leadership and key stakeholders, summarizing data trends, insights, and the impact of data initiatives on business performance. 7. Training and Data Literacy: * Foster a data-driven culture by promoting data literacy across the organization. * Lead training initiatives to increase understanding and effective use of data across departments. * Create and implement programs to help teams at all levels develop their data skills, from basic data interpretation to advanced analytics. 8. Data Innovation and Continuous Improvement: * Explore and experiment with emerging data technologies, techniques, and methodologies to continuously improve data processes and strategies. * Drive innovation within the organization by exploring new ways to leverage data for competitive advantage. * Ensure that data practices are continuously evolving and adapting to industry trends, new challenges, and the evolving business environment. Qualifications: 1.Educational Background: Bachelor's degree in Data Science, Business Analytics, Computer Science, Information Management, or a related field (Master's degree preferred). 2.Technical Skills * Proven experience with data analytics, data management, and business intelligence tools (e.g., Tableau, Power BI, Looker). * Strong knowledge of data modeling, data architecture, and data governance frameworks. * Familiarity with data processing frameworks, such as SQL, Python, R, or other programming languages used for data manipulation and analysis. * Experience with data management platforms (e.g., Hadoop, AWS, Google Cloud Platform, or Azure). * Knowledge of data security and compliance regulations (e.g., GDPR, CCPA). * Strong ability to analyze large datasets, identify trends, and provide actionable insights. * Proven experience in identifying and developing KPIs and metrics that drive business performance. * Ability to apply advanced statistical methods, machine learning algorithms, or predictive analytics models to solve complex business problems (preferred but not required). 3.Soft Skills: * Excellent communication skills, both written and verbal, with the ability to explain complex data insights to non-technical stakeholders. * Experience presenting executive leadership and guiding strategic decision-making. * The ability to translate business problems into data-driven solutions that are both practical and impactful. * Strong leadership and project management skills, with the ability to drive data initiatives across multiple teams. * Ability to work collaboratively with cross-functional teams, including business leaders, data engineers, data scientists, and IT professionals. * Comfortable working in a fast-paced, ever-evolving environment. * Ability to think strategically about how data can be used to meet business goals and drive organizational change. * Experience in developing and implementing long-term data strategies that support business transformation. 4.Experience: * Experience with advanced analytics, such as machine learning, AI, or automation in a business context. * Experience working with cloud-based data platforms (AWS, GCP, Azure) and big data solutions. * Familiarity with agile methodologies and how they can be applied to data strategy initiatives 5.Work Environment: * Collaborative and fast-paced work environment. * Opportunity to work with state-of-the-art technologies. * Supportive and dynamic te am culture Salary Range: $149,175 - $201,825 a year #LI-AD1