Data Warehouse Analyst

Job Description

Job Description

Top skills:

• Experience in metadata discovery and documentation (5+ years).
• Experience in data profiling (5+ years).
• Experience in data quality assessment and identification (5+ years).
• Advanced experience in SQL and Python (3+ years).

IMPORTANT NOTES:

• Candidate must be available to perform all work during the Central Standard Time (CST) business hours 9:00 am – 3 pm (or CST hours as defined by the hiring manager).
• Candidate will be required to provide their own equipment for this position (See job description for required specifications).

Interview process: via Zoom/Teams. 

Onsite, hybrid or remote : WI residency required. Must be WI resident or willing to relocate within 30 days of start date at own expense. 90-100% remote but can require staff to come onsite as necessary with sufficient notice. Onsite work is not likely, but candidate should be prepared to come onsite if required.

Duration: This is a limited engagement expected to end 12/31/2026, but could be extended. Cannot currently confirm the likelihood of extension.

Project details: This position will be responsible for the assessment of data quality and metadata within org's data architecture. They will be responsible for the data profiling, analysis and documentation of data quality. Experience with Human Services business intelligence is desirable.

List any special qualifications & years of experience: This position will be responsible for the assessment of data quality and metadata within org's data architecture. They will be responsible for the data profiling, analysis and documentation of data quality.

The individual in this position will:

• Audit existing databases to assess data characteristics such as completeness, accuracy, outliers, and duplicates.
• Investigate and define automated validation rules to guarantee data accuracy and catch errors at the point of entry.
• Develop data cleansing and remediation recommendations for data irregularities.
• Establish key performance indicators (KPIs) to measure data health, and build reporting dashboards to track quality metrics and trends.
• Investigate the origins of recurring data errors (e.g., system bugs, user errors, integration issues) and recommend targeted, systemic solutions.
• Document and define key metadata around database architecture.
• Make recommendations on data maintenance and data quality.
• Collaborate with Data Modelers and Data Architects on recommendations for key data management and data quality efforts.

This is a limited engagement expected to end 12/31/2026, but could be extended.

Experience with Human Services business intelligence is desirable.