Data Analyst (Contract)

Sound Physicians•,

1d•$65 - $85

About The Position

We are seeking an experienced and technically proficient Data Analyst to join our IT Data & Analytics team for a 6-month contract assignment. This role is responsible for analyzing and profiling source data, translating business needs into clear technical requirements, and supporting the delivery of reliable data integration and analytics solutions. The Data Analyst will conduct complex SQL analysis, investigate data issues, document source-to-target requirements, and collaborate closely with business stakeholders and ETL developers. This position plays a critical role in ensuring that data is accurate, well understood, and appropriately structured to support the continued growth of our enterprise data warehouse and analytics capabilities. The ideal candidate combines strong technical expertise with analytical curiosity, sound problem-solving skills, and the ability to communicate effectively across both business and technical teams. This is a 6-month, full-time contract. Applicants must be authorized to work in the United States without the need for current or future employer-sponsored work authorization.

Requirements

Bachelor's degree in Data Science, Information Systems, Computer Science, or a related field.
Minimum of three years of experience in a data analyst or comparable analytical role, preferably within a delivery-focused and analytics-driven environment.
Strong proficiency in SQL, including advanced querying techniques such as joins, subqueries, common table expressions, aggregations, and window functions.
Strong understanding of data warehousing concepts, data integration practices, and ETL processes.
Experience profiling source data and assessing data quality, completeness, consistency, and usability.
Experience documenting technical requirements, source-to-target mappings, data definitions, transformation rules, or similar specifications.
Demonstrated ability to investigate complex data issues, identify root causes, and communicate findings clearly.
Ability to translate business requirements into structured technical and analytical deliverables.
Strong attention to detail, with a commitment to producing accurate, reliable, and well-documented work.
Ability to manage multiple priorities and contribute effectively within an Agile delivery environment.

Responsibilities

Profile and analyze source data using SQL to assess data structure, completeness, quality, and alignment with business and technical requirements.
Perform advanced ad hoc querying to support data investigations, troubleshooting, solution design, and project scoping.
Translate business requirements into clear, actionable technical requirements for data integration, warehousing, and reporting solutions.
Develop and maintain source-to-target mappings, technical specifications, data definitions, and related solution documentation.
Partner with ETL developers to validate transformation logic and ensure data is appropriately structured for downstream reporting and analytical use.
Collaborate with business stakeholders to understand operational needs, clarify requirements, and translate complex business questions into practical data solutions.
Support the development and refinement of data models that promote consistency, scalability, and effective reporting.
Conduct data validation, reconciliation, and testing to confirm the accuracy, completeness, and reliability of analytical deliverables.
Identify data quality issues, investigate root causes, document findings, and collaborate with appropriate partners to support resolution.
Create and maintain comprehensive documentation of data sources, structures, relationships, definitions, transformations, and business rules.
Prepare data sets and perform targeted analysis to support ETL development, testing, and implementation activities.
Monitor data integrity and proactively surface risks, inconsistencies, and opportunities for improvement.
Participate actively in Agile delivery practices, including sprint planning, daily stand-ups, backlog refinement, estimation, testing, and retrospectives.
Communicate technical concepts, analytical findings, and data limitations clearly to both technical and nontechnical audiences.
Stay current with evolving practices in healthcare analytics, data management, data quality, and enterprise data warehousing.