Manager, Data Analytics

Manager, Data Analytics

Spire is seeking a dynamic and forward-thinking Manager, Data Analytics to lead the evolution of our enterprise analytics services and capabilities. This role will be instrumental in shaping and delivering high-impact data products, driving business intelligence strategies, and enabling scalable analytics solutions through modern data platforms and low-code technologies. This role will have a direct impact on solving business challenges by transforming the delivery and use of data to produce advanced insight across Spire.

Lead and mentor a high-performing team of data analysts, fostering a culture of curiosity, accountability, and continuous learning.

Provide coaching and guidance on analytics best practices, stakeholder engagement, and solution delivery.

Partner closely with data engineering and machine learning teams to ensure scalable, secure, and performant data infrastructure.

Interface with business stakeholders to gather requirements, define use cases, and translate needs into actionable data products and roadmaps.

Oversee the design and implementation of enterprise BI solutions using tools like Power BI, enabling self-service analytics and data democratization.

Drive adoption of data-driven decision-making across departments through intuitive dashboards and storytelling.

Champion the use of Power Apps and other low-code platforms to rapidly prototype and deploy business applications that streamline operations and improve user experience.

Act as product owner for key analytics initiatives, managing backlog, prioritizing features, and aligning delivery with strategic goals.

Define success metrics and ensure continuous improvement through stakeholder feedback and performance monitoring.

Guide the evolution of Spire's cloud data platform, including data lakes, fabric, hubs, and pipelines, to support advanced analytics and predictive modeling.

Leverage emerging technologies to incorporate machine learning and AI into analytics workflows.

Collaborate closely with the Enterprise Architecture team to ensure that Spire's data governance standards are consistently applied within the Data Cataloging systems, while also maintaining alignment between the enterprise data model and Spire's broader data strategy to support scalable analytics capabilities and accurate metadata management.

Manage project requirements, analytic plans, SOWs, project timelines, and other related materials for the management of deliverables.

Provide analytical data to stakeholders to assist the business in the decision-making process.

Serve as a mentor to support and develop team members.

All other duties as assigned

Ability to demonstrate the core and job category competencies : customer-focused, results-driven, teamwork, communications, adaptability, initiative, problem solving and quality.

Ability to lead by example in support of the Company's essential characteristics and values : strong ethics and integrity, dedication to a safe work environment, commitment to a diverse workforce that recognizes and respects every individual's unique skills and perspectives.

Proven experience leading analytics teams and delivering enterprise BI solutions.

Strong understanding of data engineering principles and ML and data workflows.

Demonstrated success in stakeholder engagement and product management.

Expertise in Power BI, Power Apps, and cloud data platforms (e.g., Oracle, Azure, AWS).

Excellent communication, strategic thinking, and problem-solving skills

Yes

Bachelor of Science in Computer Science, Information Systems / Technology, or related area or Bachelor of Arts in Business, or related field (Equivalent work experience is acceptable) Master's degree preferred

8 years of experience working with Analytics, Business Intelligence or Software Development teams Expert knowledge in Business Intelligence tools (e.g., Power BI, Tableau etc.). Experience with Low-code development platforms (e.g., Power Apps, Power Automate). Experience with Cloud data platforms (e.g., Azure Data Lake, Fabric, Synapse, Data Factory, Databricks). Strong experience in building business stakeholder relationships including through Data product ownership and data product lifecycle management and stakeholder engagement. Knowledge of Machine learning and AI model development and deployment. Knowledge of DevOps / MLOps practices (e.g., CI / CD pipelines, Azure DevOps, GitLab). Agile methodologies (e.g., Scrum, iterative development). Understanding of data management, cleansing, data warehousing, data lakes, data factories and data hubs Experience with Programming and scripting : SQL, Python, R, JavaScript, XML. Experience with Statistical and mathematical concepts : Regression, segmentation, optimization, A / B testing. Experience with Agile development and delivery of projects in an agile manner Detail-oriented and organized, with a proactive problem-solving mindset and abilities

Hybrid work environment Travel 15%