Data Operations Analyst
New
USFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2+ years
- Required Skills
- SQLETLMicrosoft Power BITableauAzureMicrosoft ExcelDatabricksLookerAzure DevOps
Requirements
- Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Business, or a related field (or equivalent experience).
- 2+ years of experience in data operations, data analysis, or business systems analysis roles.
- Hands-on experience with SQL and cloud-based data environments such as Databricks and Azure.
- Understanding of ETL/ELT pipelines, data warehousing concepts, and data integration processes.
- Experience with data validation, data quality assurance, and ensuring system-wide data consistency.
- Strong ability to gather, document, and translate business and technical requirements.
- Proficiency in Excel, including pivot tables, VLOOKUPs, and advanced formulas.
- Experience with data visualization tools such as Tableau, Power BI, or Looker is a plus.
- Strong analytical, problem-solving, and organizational skills with high attention to detail.
- Excellent communication skills with the ability to bridge technical and non-technical audiences.
- Familiarity with Python, APIs, or Azure DevOps is a plus.
- Experience in healthcare or regulated data environments is an added advantage.
Responsibilities
- Collaborate with business stakeholders to gather, document, and translate data and reporting requirements into structured workflows.
- Work cross-functionally with Product, Engineering, Analytics, and Client Delivery teams to improve data processes and systems.
- Use SQL and related tools to support reporting, dashboards, and data extraction for decision-making.
- Ensure data accuracy, consistency, and integrity through validation, reconciliation, and quality assurance checks.
- Perform file testing and data verification during implementations to ensure compliance with specifications.
- Conduct root cause analysis on data issues and support the implementation of long-term process improvements.
- Troubleshoot data and application issues, documenting findings and recommending corrective actions.
- Support and optimize data workflows and pipelines within platforms such as Databricks and Azure DevOps.
- Contribute to automation and process optimization initiatives to improve operational efficiency.
- Maintain clear documentation of data processes, definitions, and workflows for stakeholders and teams.
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