Senior Business Consultant - Data Management

Description :

Role : Senior Business Consultant - Data ManagementLocation : San Francisco, CAResponsibilities : 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 initiatives5.Work Environment :
• Collaborative and fast-paced work environment.
• Opportunity to work with state-of-the-art technologies.
• Supportive and dynamic team culture#LI-AD1