Darshini Priya
Data Engineer at Knoema- Claim this Profile
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Bio
Credentials
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Python for Data Science
IBMAug, 2023- Nov, 2024
Experience
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Knoema
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United States
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Software Development
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1 - 100 Employee
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Data Engineer
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Dec 2022 - Present
1. Data Integration: Integrate data from various sources into a unified format suitable for analysis. Use Excel and Python Pandas to clean, transform, and preprocess data as needed. 2. Database Management: Design and maintain databases, ensuring data integrity, availability, and security. 3. ETL (Extract, Transform, Load): Develop and maintain ETL processes to move datafrom source to data warehouse. 4. Statistical Analysis: Perform basic statistical analysis using Excel, including calculating means, medians, standard deviations, and correlations. 5. Data Visualization: Create charts, graphs, and dashboards in Excel and Power BI to effectively communicate findings to stakeholders. 6. Data Interpretation: Transformations of complex data sets into understandable and actionable insights for non-technical stakeholders. 7. Collaboration: Collaborate with Data Analysts to understand data requirements and assist in preparing data for analysis in Excel. 8. Business Alignment: Understand business objectives and use Excel and Python to support decision-making processes through data-driven insights. Show less
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Knoema
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United States
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Software Development
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1 - 100 Employee
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Data Engineer
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Mar 2021 - Jun 2022
1. Data Collection: Gather and extract data from various sources, including databases, and external systems. 2. Data Transformation: Clean, preprocess, and transform raw data into a structured format suitable for analysis and modeling. 3. Data Integration: Integrate and consolidate data from multiple sources, ensuring data consistency and accuracy. 4. Database Design: Design, create, and maintain databases optimized for data storage and retrieval, considering performance and scalability requirements. 5. ETL (Extract, Transform, Load) Processes: Develop and manage ETL pipelines to efficiently extract, transform, and load data into the data warehouse or other target systems. 6. Data Modeling: Design and implement data models to support analytics and reporting needs, ensuring data integrity and efficient querying. 7. Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver solutions that meet their needs. 8. Documentation: Document data engineering processes, data flows, and technical specifications to facilitate knowledge sharing and ensure system maintainability. Show less
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Education
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2017 - 2020
Tumkur University
Vidyavahini first grade college, Computer Science
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