Data Analyst Jobs in Des Moines, WA

About The Position

Requirements

• At least 5 years of experience in data analysis, business analysis, data products, analytics consulting, or enterprise solution delivery.
• Demonstrated experience translating business needs and operational processes into functional requirements, business rules, acceptance criteria, and data specifications.
• Strong experience with data discovery, profiling, data quality assessment, testing, business validation, and solution adoption.
• Proficiency with SQL, data analysis techniques, and enterprise analytical tools.
• Experience working with cross-functional business, product, technology, and data teams.
• Experience supporting business process automation, workflow solutions, or AI-enabled capabilities and translating business requirements into actionable solution designs.
• Understanding of enterprise data platforms, integration patterns, analytics, AI, metadata, and automation technologies.
• Strong customer engagement, communication, facilitation, problem-solving, and stakeholder management skills.
• If working from home occasionally or permanently, an internet connection through cable broadband or fiber optic service with at least 10 Mbps download and 5 Mbps upload is required.

Nice To Haves

• Experience with Databricks or comparable cloud data platforms and data product development initiatives.
• Experience with workflow automation platforms, low-code solutions, process mining, or AI-enabled business solutions.
• Knowledge of metadata management, data governance practices, and enterprise data architecture concepts.
• Experience in healthcare, insurance, or another highly regulated industry.
• Experience in complex, regulated enterprises is preferred.

Responsibilities

• Partner with business stakeholders to understand objectives, operational processes, decision-making needs, desired outcomes, and how data supports them.
• Facilitate discovery sessions, requirements workshops, and stakeholder interviews; translate customer needs into functional requirements, business rules, acceptance criteria, and value measures.
• Document business context, intended use, process requirements, and expected outcomes before solution development begins.
• Perform data discovery, profiling, and analysis to assess data quality, completeness, metadata, usability, and fitness for purpose; identify gaps and remediation needs early.
• Define and document business semantics, data definitions, transformation logic, source-to-target mappings, data relationships, and readiness criteria.
• Develop clear functional and data requirements that enable efficient solution development.
• Partner with Data Operations and Data Engineering during design and delivery to ensure solutions reflect business intent and support reuse.
• Develop analytical datasets, reusable data assets, and Gold layer data solutions when analyst-led development can effectively address business requirements.
• Develop and execute functional tests and test cases, and conduct business acceptance validation for engineered datasets, data products, and integrated solutions.
• Coordinate customer feedback, user acceptance testing, adoption, and transition activities to integrate solutions into business workflows.
• Assess business processes for workflow improvement, simplification, and operational efficiency opportunities.
• Identify opportunities to use data, workflow automation, AI, or integrated solutions to improve processes, efficiency, and customer outcomes.
• Partner with automation, AI, DataOps, and Technology teams to define requirements, validate solutions, and measure realized business value when automation is appropriate.
• Develop analytical solutions, prototypes, and business insights when customer needs can be met without extensive engineering investment.
• Support rapid proof-of-concept and learning-stage work while establishing a pathway to enterprise-scale operationalization where needed.
• Prepare documentation, training, and knowledge-transfer materials to enable customer adoption and use of data products, integrated solutions, and automated workflows.
• Use AI, metadata, workflow, and reusable analytical patterns to improve requirements discovery, data profiling, documentation, testing, and traceability.
• Develop reusable templates, requirements assets, testing approaches, and documentation standards to improve consistency and delivery speed.
• Contribute to repeatable operating practices that reduce manual effort and improve quality throughout the solution lifecycle.

Benefits

• Annual bonus plan eligibility anticipated.
• Medical benefits.
• Vision insurance.
• Dental insurance.
• Well-being and behavioral health programs.
• 401(k).
• Company-paid life insurance.
• Tuition reimbursement.
• At least 18 days of paid time off per year.
• Paid holidays.
• Leaves of absence.