
Data Analysis Specialist
1 week ago
Data analysis is a vital component of business decision-making. As a data analyst, you will be responsible for the day-to-day management and maintenance of data infrastructure, including data ingestion, storage, organization, and retrieval processes.
Key Responsibilities:
- Monitor and assess the quality of stored data, identify inconsistencies, errors, and gaps, and collaborate with relevant stakeholders to address data quality issues.
- Develop and implement data integration and transformation pipelines to ingest, cleanse, and transform data from various sources into the data infrastructure, ensuring compatibility and consistency.
- Implement and enforce data governance policies and security measures to safeguard sensitive and confidential data stored in the data infrastructure, in compliance with regulatory requirements and best practices.
- Identify opportunities to optimize the performance and efficiency of the data infrastructure, including storage optimization, query performance tuning, and resource utilization monitoring.
- Conduct exploratory data analysis and perform ad-hoc queries to extract insights and derive actionable intelligence from the data infrastructure, supporting decision-making processes across the organization.
- Maintain comprehensive documentation of data processes, configurations, and workflows, and generate regular reports on data performance, usage metrics, and data quality metrics.
Requirements:
- Bachelor's degree or higher in Computer Science, Information Systems, Statistics, Mathematics, or a related field.
- Skilled in using specific tools for data analysis, including Microsoft Fabric, Azure Synapse Analytics for big data and complex analysis tasks, and Microsoft Power BI for data visualization and business intelligence solutions.
- Proficiency in SQL and experience with database management systems (DBMS) for querying, manipulating, and analyzing large datasets.
- Strong analytical and problem-solving skills, with the ability to interpret complex data sets, identify patterns, and draw meaningful insights.
- Familiarity with data modeling concepts, data warehousing principles, and ETL (Extract, Transform, Load) processes.
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