Senior Data Management Professional
J
JobgetherHealthcare
Based in the United StatesFull-TimeSenior
SalaryAnnual base salary of $78,400–$107,800
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Job Details
- Experience
- At least 5 years of professional experience using Python
- Required Skills
- PythonSQLGitMachine LearningMicrosoft Power BIDatabricksAzure DevOps
Requirements
- Bachelor's degree in a technical field (Computer Science, Data Science, IT, Statistics, Engineering).
- At least 5 years of professional experience using Python for data analysis, quality, or management.
- At least 2 years of experience applying statistics and machine learning techniques.
- At least 2 years of experience building dashboards and reporting solutions, preferably with Power BI.
- Strong SQL and data analysis capabilities for working with complex datasets.
- Experience developing data solutions, scripts, queries, and analytical workflows.
- Strong problem-solving and root-cause analysis skills.
- Excellent communication skills for presenting technical findings.
- Strong organizational skills and ability to manage multiple priorities.
- Collaborative mindset with interest in process improvement.
- Must maintain a dedicated workspace and reliable internet (25 Mbps download / 10 Mbps upload).
- Ability to travel occasionally for training or meetings.
Responsibilities
- Develop, maintain, and improve data management processes and technical solutions using Python, SQL, Databricks notebooks, Azure DevOps pipelines, Power BI dashboards, and process automation.
- Analyze complex data challenges to identify data quality issues, process limitations, and improvement opportunities.
- Conduct detailed research and analysis to identify trends, inconsistencies, and operational gaps.
- Investigate data issues, conduct root cause analysis, and recommend practical resolutions for internal and external partners.
- Design and implement improvements to data processes, workflows, reporting solutions, and data quality practices.
- Develop clear and actionable dashboards and reporting solutions for stakeholder decision-making.
- Apply statistical and analytical techniques, including machine learning methods, to identify patterns.
- Present analytical findings and recommendations to technical and non-technical stakeholders.
- Manage multiple priorities and projects independently with high attention to detail.
- Support data integrity and compliance initiatives within a healthcare environment.
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