Job Description:
1. Data Extraction: Identify and understand data sources, both internal and external, and develop processes to extract data from these sources while adhering to data quality and security standards.
2. Data Transformation: Design and implement data transformation logic to cleanse, normalize, and enrich the extracted data. This includes data mapping, data validation, data aggregation, and applying business rules as necessary.
3. ETL Pipeline Development: Build and maintain ETL pipelines using industry-standard tools and frameworks. This involves scripting, coding, and utilizing ETL tools to automate the extraction, transformation, and loading of data.
4. Data Quality and Governance: Ensure data quality throughout the ETL process by performing data profiling, data validation, and implementing data quality checks. Collaborate with data governance teams to adhere to data standards and ensure compliance with data regulations.
5. Performance Optimization: Identify opportunities to optimize ETL processes for improved performance and scalability. Monitor and fine-tune ETL jobs, troubleshoot performance bottlenecks, and optimize data workflows.
6. Documentation: Create and maintain technical documentation, including data flow diagrams, data mappings, ETL process workflows, and standard operating procedures. Document data sources, transformation rules, and data lineage for effective knowledge sharing and future reference.
7. Collaboration: Collaborate with different teams to understand their data requirements and translate them into effective ETL processes. Work in cross-functional teams to deliver data solutions aligned with business objectives.
8. Continuous Improvement: Stay updated with industry trends and emerging technologies related to data integration and ETL. Proactively identify opportunities to improve data integration processes, tools, and methodologies to enhance efficiency and effectiveness.