Data Analyst (AI & Data Platform) Full Time

Everbridge is seeking a Data Analyst to help transform complex business and operational data into clear, actionable insights. This role will support reporting, workforce analytics, operational analytics, KPI tracking, forecasting, and cross-functional business intelligence initiatives.

The Data Analyst will work closely with business stakeholders, analytics engineers, data engineers, and leadership teams to build trusted reporting solutions, validate business logic, improve data quality, and support data-driven decision-making across the organization.

The ideal candidate has strong analytical fundamentals, advanced SQL skills, experience with modern cloud analytics platforms, and the ability to communicate insights clearly to both technical and non-technical audiences. This role is well suited for someone who is detail-oriented, curious, comfortable working with evolving data workflows, and interested in using automation and AI-assisted analytics tools to improve productivity, reporting quality, and operational efficiency.

What You’ll Do

• Analyze large and complex datasets to identify trends, anomalies, risks, and business opportunities.
• Build, maintain, and improve dashboards, recurring reports, and self-service analytics solutions.
• Write efficient SQL queries to support business reporting, ad hoc analysis, and data validation.
• Partner with analytics engineering and data engineering teams to validate and consume curated datasets.
• Assist in designing, testing, and validating data models used in reporting and analytics workflows.
• Translate business questions into measurable KPIs, analytical frameworks, and reporting requirements.
• Perform data quality checks, investigate reporting inconsistencies, and support root cause analysis.
• Document business logic, metric definitions, data sources, reporting methodologies, and assumptions.
• Support workforce analytics, headcount reporting, workforce movement analysis, forecasting, and operational reporting.
• Collaborate with stakeholders across Finance, HR, Operations, Product, and business leadership.
• Identify opportunities to automate manual reporting processes and improve analytics scalability.
• Support automation initiatives that reduce repetitive work and improve reporting consistency.
• Use AI-assisted tools where appropriate to support analysis, documentation, workflow development, and reporting efficiency.
• Validate AI-assisted outputs using strong analytical judgment, business context, and data quality standards.
• Contribute to the continuous improvement of reporting standards, analytics processes, and data governance practices.

What You’ll Bring

• 2-5 years of experience in data analytics, business intelligence, reporting, or a related analytical role.
• Strong proficiency in SQL for data extraction, transformation, analysis, and validation.
• Experience working with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Azure Synapse.
• Experience building dashboards and reports using BI tools such as Tableau, Power BI, Looker, or AWS QuickSight.
• Strong understanding of relational databases, data modeling concepts, and analytical data structures.
• Ability to work with large datasets, complex business logic, and multiple data sources.
• Strong analytical, problem-solving, and critical-thinking skills.
• High attention to detail and commitment to data accuracy.
• Ability to manage ad hoc analysis requests while balancing recurring reporting priorities.
• Strong communication skills, with the ability to explain data findings to technical and non-technical audiences.
• Experience working with business stakeholders to gather requirements and translate them into reporting solutions.
• Ability to document assumptions, methodologies, business rules, and reporting logic clearly.

Preferred Experience

• Experience in supporting HR, workforce, finance, operations, or SaaS business analytics.
• Experience with modern data transformation tools such as dbt.
• Familiarity with ETL/ELT pipelines and modern data stack architecture.
• Understanding of data governance, data quality, and reporting standardization best practices.
• Experience working with APIs, SharePoint data sources, or automated data ingestion workflows.
• Exposure to Python or other scripting languages for automation and data analysis.
• Experience working with Git or version-controlled analytics workflows.
• Exposure to knowledge graphs, entity relationship modelling, or semantic data structures, especially as applied to workforce analytics, business reporting, data discovery, or AI-assisted analytics workflows.
• Familiarity with AI-assisted analytics tools, generative AI copilots, automated insight generation, or workflow automation platforms.

Nice-to-Have Skills

• Experience using AI tools for general productivity, including drafting documentation, summarizing information, improving workflows, and accelerating routine analytical tasks.
• Experience using AI-assisted development tools or coding copilots to support SQL writing, scripting, debugging, documentation, or analytics workflow development.
• Familiarity with using AI to support automation, such as generating scripts, streamlining recurring reporting tasks, creating data validation checks, or improving manual business processes.
• Experience working in Agile analytics, product analytics, or cross-functional delivery teams.
• Curiosity about emerging analytics technologies, workflow automation, and AI-enabled business intelligence.

Technical Environment

• Snowflake
• SQL
• dbt
• Tableau
• Power BI
• AWS QuickSight
• Cloud-based analytics platforms
• Workforce and operational reporting datasets
• SharePoint and other business data sources
• Git and version-controlled analytics workflows
• AI-assisted productivity, development, and analytics tools

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.