Data Analyst
Data Analysts are employed across diverse industries including federal agencies like the National Geospatial-Intelligence Agency (NGA), environmental consulting firms, healthcare organizations, utilities and energy companies, engineering and infrastructure firms, financial institutions, and technology startups. They support missions in national security, public health, environmental monitoring, market analysis, workforce planning, and operational optimization. The career outlook for Data Analysts remains exceptionally strong, with demand driven by the continued growth of big data, cloud computing, artificial intelligence, and the increasing recognition that data-driven insights provide competitive advantages and improve organizational outcomes.
Salary by Seniority Level
P25 = 25th percentile, P75 = 75th percentile. Based on listed salary ranges from job postings.
What to Expect at Each Level
Entry Level
Entry-level Data Analysts typically focus on data collection, cleaning, and basic analysis under the supervision of senior team members. They execute established procedures for data quality assurance, create standard reports and dashboards, perform routine statistical analyses, and maintain databases and data management systems. These professionals learn organizational data structures, become proficient in analytical tools and software platforms, and develop foundational skills in SQL, Excel, and visualization applications. They often support specific projects by gathering requirements, documenting processes, and assisting with the preparation of findings for internal stakeholders while building domain knowledge in their industry or technical specialty.
Mid Level
Mid-level Data Analysts take ownership of complete analytical projects from conception through delivery, independently designing analytical approaches and selecting appropriate methodologies for complex business questions. Their responsibilities expand to include developing automated data pipelines, creating sophisticated visualizations and interactive dashboards, conducting advanced statistical modeling, and translating technical findings into clear recommendations for non-technical audiences. They collaborate across departments to identify data needs, mentor junior analysts, contribute to process improvements, and may begin specializing in areas such as geospatial analysis, predictive modeling, financial analytics, or specific industry applications. These professionals are expected to proactively identify opportunities where data analysis can add value and communicate insights that influence operational decisions.
Senior Level
Senior Data Analysts serve as subject matter experts who lead major analytical initiatives, establish best practices, and provide technical guidance to teams. They design complex analytical frameworks, develop innovative methodologies to address novel business challenges, and oversee the quality and integrity of high-stakes analyses that inform strategic decisions. Their role combines deep technical expertise in advanced analytics, database architecture, and statistical techniques with strong business acumen that enables them to align analytical work with organizational priorities. Senior analysts often manage relationships with key stakeholders, present findings to executive leadership, evaluate and implement new analytical tools and technologies, and may supervise small teams while contributing to departmental strategy and capability development.
Leadership
Leadership-level Data Analysts hold positions such as Director of Analytics, Chief Data Officer, or Analytics Program Manager, where they define organizational data strategy, build analytical capabilities, and ensure data-driven decision-making becomes embedded in organizational culture. They oversee analytics teams, establish governance frameworks, set standards for data quality and security, and align analytical investments with enterprise objectives. These professionals operate at the intersection of technology, business strategy, and organizational change management, championing the value of analytics across the organization, securing resources for analytical initiatives, and partnering with executive leadership to identify how data and analytics can drive competitive advantage, operational excellence, and mission success. They are responsible for building high-performing teams, fostering innovation in analytical methods, and demonstrating measurable business impact from analytics investments.