Sr Data Analytics Manager

As a Sr Data Analytics Manager here at Honeywell, you will play a crucial role in driving data-driven insights and analytics to optimize operational efficiency and improve decision-making within the organization. You will lead a team of analytics professionals, collaborating with cross-functional teams to identify business challenges and develop analytical solutions. With your strong leadership skills and expertise in data analytics, you will develop and implement data analytics strategies to drive continuous improvement. Your ability to translate complex data into actionable insights will be key in ensuring data integrity and accuracy. In this role, your work will improve decision making in the business, optimize processes, increase cost savings, and improve customer satisfaction.You will report directly to our Director IT and you’ll work out of our Atlanta, US location on a [3:2] work schedule.In this role, you will impact the organization by:

Leading the development and execution of a comprehensive data strategy for the organization, including data collection, storage, and maintenance, to facilitate data-driven decision-making.

Utilizing statistical and data analysis techniques to extract meaningful insights from various data sources, providing actionable recommendations to improve efficiency and cost-effectiveness.

Collaborating with cross-functional teams to align data analytics with overall business goals and strategies.

Identifying and implementing advanced analytics tools and technologies to support data visualization, reporting, and monitoring of key performance indicators.

Driving a culture of continuous improvement by analyzing and optimizing processes, identifying areas for automation and efficiency gains.

Proactively identifying and mitigating risks through data analysis, ensuring business continuity and resilience.

Leading a team of analysts, providing mentorship and guidance while fostering a culture of innovation and growth.

Key Responsibilities

Strategic Planning and Leadership

Developing Data Strategy: Creating and implementing strategies for data collection, storage, analysis, and usage that align with business goals.

Leadership and Team Management: Leading and managing a team of data analysts, data scientists, and other data professionals. Providing guidance, mentorship, and career development opportunities for the team.

Stakeholder Collaboration: Working closely with other departments, including IT, marketing, finance, and operations, to understand their data needs and ensure alignment with business objectives.

Data Management

Data Governance: Establishing and maintaining data governance policies to ensure data quality, consistency, and security across the organization.

Data Integration: Overseeing the integration of data from various sources, ensuring it is accurate, consistent, and accessible.

Data Warehousing: Managing data warehousing solutions and ensuring that data is properly stored and easily retrievable.

Analytics and Insights

Advanced Analytics: Leading efforts in advanced analytics, including predictive modeling, machine learning, and statistical analysis to derive actionable insights.

Reporting and Visualization: Developing dashboards, reports, and visualizations that effectively communicate insights to stakeholders.

Business Intelligence (BI): Overseeing the implementation and use of BI tools to support decision-making processes across the organization.

Technology and Tools

Tool Selection: Evaluating and selecting appropriate data management and analytics tools, ensuring they meet the organization’s needs.

System Implementation: Managing the implementation of data platforms, analytics tools, and other relevant technologies.

Automation: Identifying opportunities to automate data collection, processing, and analysis to improve efficiency.

Data Quality and Compliance

Ensuring Data Quality: Implementing processes to ensure data accuracy, completeness, and reliability.

Compliance: Ensuring that data practices comply with relevant regulations, such as GDPR, HIPAA, or other industry-specific standards.

Risk Management: Identifying and mitigating risks associated with data management and analytics, such as data breaches or loss of data integrity.

Performance Monitoring and Reporting

Key Performance Indicators (KPIs): Defining and monitoring KPIs related to data and analytics initiatives to measure their impact on business outcomes.

Continuous Improvement: Continuously evaluating and improving data processes, analytics methodologies, and tools to enhance performance.

Innovation and Research

Staying Current: Keeping up with the latest trends and technologies in data and analytics to ensure the organization remains competitive.

Pilot Projects: Leading pilot projects to test new analytics methods, tools, or data sources that could add value to the business.

Budgeting and Resource Allocation

Budget Management: Managing budgets for data and analytics projects, ensuring resources are allocated effectively and within financial constraints.

Vendor Management: Negotiating contracts and managing relationships with third-party vendors and service providers.

YOU MUST HAVE 8+ years of experience in data analytics. Experience leading and coaching direct or indirect reports. Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights. Proficiency in data analytics tools and programming languages (e.g., Python, R, SQL, etc.). Experience with data visualization tools (e.g., Tableau, Power BI, etc.) Experience with data warehouse applications like Snowflake Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.WE VALUE Bachelor's degree in a relevant field (e.g., Data Science, Analytics, Engineering, etc.). Strong leadership skills and the ability to effectively influence and coach others. Proven track record of driving data-driven decision-making and delivering measurable business results. Experience in data analytics or related field. Knowledge of advanced analytics techniques (e.g., machine learning, predictive modeling, etc.). Experience with data governance and data quality initiatives.#LI-Hybrid Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.