Senior Risk Data Analyst

SBA Communications•Boca Raton, FL

18h

About The Position

Since 1989, SBA Communications has been a pillar of the wireless industry. Today, as a publicly traded global leader and S&P 500 company, our network of over 46,000 communication sites spans 10+ countries, forming the critical infrastructure that connects millions. We are the force behind the scenes —the essential infrastructure that keeps our world connected. We are looking for innovators to join the dynamic team that makes it all possible. In an industry that moves fast, we rely on our agility to stay ahead of the curve and deliver results. However, we never achieve it alone. Our culture is defined by a "Team First" focus, where every team member matters, and we collaborate passionately to support our customers' objectives. We believe in shared success. At SBA, we invite every team member to think like an owner. Financial Wellbeing: Plan for your future with our Global Ownership Program (Annual RSU awards for eligible employees), a 401K with a generous company match, and an Employee Stock Purchase Plan offering company stock at a discount. Mental Wellbeing: We prioritize your health with access to a dedicated Health Concierge service. Personal Growth & Balance: Enjoy a generous Paid Time Off (PTO) package, paid holidays, and paid volunteer hours. We also fuel your ambition with tuition reimbursement, support for professional certifications, and a wellness reimbursement program. If you’re ready to make an impact with a stable industry leader, we want to hear from you. Your Next Career Opportunity – Senior Data Analyst – Risk Insights & Dashboarding The Senior Data Analyst will lead the development of risk dashboards and insights that support strategic decision-making across controlled processes. This role requires deep expertise in Power BI, data modeling, and risk analytics, along with the ability to collaborate with IT to ingest and manage data within the enterprise data lake. The analyst must also possess strong financial and audit risk acumen to build meaningful models and tell compelling stories through data.

Requirements

Bachelor’s or Master’s degree in Data Science, Finance, Accounting, Computer Science, or related field.
5+ years of experience in data analytics, preferably in risk, audit, or financial environments.
Advanced proficiency in Power BI, SQL, and data visualization techniques.
Strong understanding of financial principles and audit risk frameworks (e.g. SOX, COSO).
Experience working with IT teams to manage data pipelines and data lake architecture.
Ability to craft compelling data stories and present insights to technical and non- technical audiences.
Excellent communication, stakeholder engagement, and project management skills

Nice To Haves

Experience with enterprise audit platforms and GRC tools.
Familiarity with machine learning techniques for risk forecasting.
Knowledge of regulatory environments and enterprise risk management systems.

Responsibilities

Design and maintain enterprise-level dashboards that visualize risk metrics, control effectiveness, and audit outcomes using Power BI.
Partner with IT teams to ensure seamless data ingestion into the data lake, including defining data requirements and validating data pipelines.
Build and maintain semantic models and self-service analytics layers to support audit and risk teams.
Develop predictive and descriptive models that support risk profiling and controlled process design.
Translate complex datasets into clear, actionable insights and narratives for senior leadership.
Ensure data quality, governance, and compliance with internal standards and regulatory requirements.
Establish and uphold best practices for responsible AI use, including model transparency, ethical data handling, and bias mitigation.
Oversee governance frameworks for the enterprise data warehouse, ensuring data integrity, security, and compliance with regulatory standards.
Contribute to the development of analytics frameworks and best practices.
Collaborate with finance, audit, compliance, and operations teams to align analytics with business objectives.