Sr. Data Analyst

Arch Insurance Group Inc.•Washington, DC

3d•$90,000 - $120,000•Hybrid

About The Position

The Senior Data Analyst is a hands-on analytical and technical contributor on Arch Mortgage’s Data, Reporting and Insights team. The role supports the team’s mission to unlock the power of data through accurate, timely, and actionable reporting and analytics that help stakeholders make data-driven decisions. The analyst builds and supports reliable data pipelines, analytics-ready data assets, reports, dashboards, and insights using modern platforms such as Databricks, Snowflake, and Azure. The role partners with business stakeholders to understand objectives, translate requirements into practical data solutions, and deliver accurate, reusable, and well-documented work. The position also contributes to ongoing innovation and quality by using cloud-based data and analytics platforms, automation, and AI-assisted development tools. The analyst follows established development practices, troubleshoots data and performance issues, and shares knowledge and expertise with colleagues. The work environment is a normal office environment with a hybrid schedule of two days in the office and three days working remotely. The position is incentive eligible, with a stated base salary range of $90,000–$120,000 per year.

Requirements

Strong analytical, critical-thinking, and problem-solving skills, including the ability to identify trends, patterns, risks, and opportunities in complex datasets.
Proficiency in SQL, Python, and modern data analytics, automation, and reporting techniques.
Knowledge of data warehousing, data modeling, data integration, and analytics solution design principles.
Strong understanding of cloud-based data and analytics ecosystems and the ability to develop and support scalable solutions using modern platforms and technologies.
Experience using business intelligence, data visualization, and analytical tools to communicate insights and support decision-making.
Familiarity with AI-assisted productivity and analytics tools and the ability to use them effectively to improve quality, efficiency, and outcomes.
Ability to translate business requirements into effective data and analytics solutions and communicate complex concepts to technical and non-technical audiences.
Strong organizational, prioritization, and collaboration skills, including the ability to manage multiple initiatives and competing priorities.
Bachelor’s degree in Information Systems, Business Analytics, Data Science, Computer Science, Engineering, Mathematics, Statistics, Economics, Finance, or a related discipline; or an equivalent combination of education and relevant experience.
At least 3 years of progressive experience in data analytics, reporting, business intelligence, data engineering, or related disciplines, including independently delivering data and analytics solutions and partnering with business stakeholders.

Nice To Haves

Experience with Databricks, Snowflake, and modern cloud-based analytics platforms.

Responsibilities

Design, develop, and support data pipelines, analytical datasets, reports, dashboards, and automation that enable business decision-making.
Acquire, integrate, transform, and validate data from internal and external sources, ensuring it is accurate, consistent, secure, and accessible.
Perform data analysis, modeling, reconciliation, and trend evaluation to identify actionable insights, opportunities, risks, and recommendations.
Partner with business stakeholders to understand objectives, gather requirements, and translate business needs into scalable data and analytics solutions.
Manage multiple priorities and communicate progress, risks, dependencies, and recommendations to stakeholders and leadership.
Use modern cloud-based data and analytics platforms, automation technologies, and AI-assisted development tools to improve productivity, delivery speed, and solution quality.
Apply testing, documentation, version control, peer review, and change management practices to ensure reliable, maintainable, and scalable solutions.
Troubleshoot data, process, and performance issues, identify root causes, and implement resolutions while improving existing solutions.
Serve as a subject matter resource in assigned business domains and support team success through knowledge sharing, documentation, collaboration, and informal mentoring.