Job Summary:
A Data Integration Engineer is responsible for designing, developing, and maintaining data integration solutions within an organization. They work closely with various stakeholders, including business analysts, data scientists, and software developers, to ensure the smooth flow of data between different systems, databases, and applications. Their primary objective is to create productive, reliable, and scalable data integration pipelines that enable accurate data analysis and reporting.
Responsibilities:
- Data Source Identification: Identify and understand the various data sources within the organization, which may include databases, applications, external APIs, flat files, and more.
- Data Extraction: Extract data from source systems using ETL (Extract, Transform, Load) processes, or through real-time data streaming technologies.
- Data Transformation: Clean, transform, and enrich the data to ensure it meets the quality and formatting requirements of the target system. This may involve data cleansing, data validation, and data standardization.
- Data Integration:
Integrate data from multiple sources into a central data repository or data warehouse, ensuring that the data is consistent and accurate.
- ETL Development: Develop and maintain ETL (Extract, Transform, Load) processes, scripts, and workflows to automate data integration tasks.
- Data Mapping: Create data mapping documents to define how data elements from source systems correspond to data elements in the target system.
- Data Quality Assurance: Implement data quality checks and validation rules to identify and correct data quality issues during the integration process.
- Performance Optimization: Optimize data integration processes for performance and efficiency, especially in scenarios involving large datasets.
- Data Modeling: Collaborate with data architects to design and implement data models that support the integration process and ensure data consistency.
- Data Governance: Enforce dat
📌 Data Integration Engineer I (Noida)
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📍 Noida