Data Analyst

The Data Engineer/Analyst collaborates with clients, data scientists, and software engineers to develop and optimize data pipelines, ETL processes, and database structures that support IRS compliance activities. The role involves identifying and integrating data sources, enhancing data quality and accessibility, and creating scalable solutions to extract insights on payment collections and taxpayer behaviors. This position ensures that analytical models and data solutions are validated and prepared for deployment within agency functions.

This position aligns with Cayuse’s core values of Innovation, Excellence, Collaboration, Adaptability, and Integrity by fostering technical solutions that meet customer needs, promoting teamwork, and prioritizing quality in deliverables.

• →Meets with Government clients to understand business needs, define data engineering and analysis objectives, identify data sources, and develop robust data integration and processing workflows.
• →Design and implement data pipelines, ETL processes, and database structures to automate and scale data analysis solutions for client needs.
• →Perform data cleaning, transformation, and exploratory analysis to ensure data integrity and readiness for reporting and machine learning applications.
• →Work with teams of data scientists and software engineers to build scalable, reliable data pipelines to enable machine learning models and business intelligence applications.
• →Develop and maintain models and views for seamless data access, visualization, and analysis.
• →Optimize data storage, indexing, and query performance to support efficient decision making, and present findings and solutions to clients. 
• →Demonstrate superior verbal and written communication skills, with the ability to explain complex analytical concepts to stakeholders with technical and non-technical backgrounds
• →Takes ownership of tasks and develops high-quality work products with minimal supervision
• →Other duties as assigned.

• Bachelor’s in Economics, Statistics, Mathematics, Computer Science, or other quantitative field, or equivalent experience.
• 2–5 years of experience in data engineering, database management, and analytical. methodologies, including designing and optimizing data pipelines and ETL processes.
• Demonstrable experience designing and implementing data processing solutions with relational or unstructured data to facilitate analytical applications.
• Experience with structured databases and query languages (e.g., PL/SQL, Postgres, MySQL), including optimization of SQL queries.
• Demonstrable experience with distributed data processing frameworks such as Spark or Hadoop preferred.
• Familiarity with statistical programming languages such as SAS, R, or Stata is helpful, but not required.
• Experience with at least one object-oriented programming language (e.g., Python, Java, Scala).
• This position requires candidates to obtain a Public Trust Clearance.
• Due to the nature of work, U.S. Citizenship is required.
• Must be able to pass a background check. May require additional background checks as required by projects and/or clients at any time during employment.

• Comfortable working on projects and with teams with heavy technical focus, including data analytics, machine learning, and/or business intelligence technologies.
• Strong collaboration skills and ability to work well in a team environment.
• Excellent verbal and written communication skills.
• Able to synthesize information from client and team needs into concrete, actionable work products and/or analytical plans.
• Strong client and team interaction skills.
• Critical thinker with excellent attention to detail.

• Professional remote office environment.
• Must be physically and mentally able to perform duties extended periods of time.
• Ability to use a computer and other office productivity tools with sufficient speed to meet the demands of this position.
• Must be able to establish a productive and professional workspace.
• Must be able to sit for long periods of time looking at computer screen.
• May be asked to work a flexible schedule which may include holidays.
• May be asked to travel for business or professional development purposes.
• May be asked to work hours outside of normal business hours.