SQL-ETL Developer

SQL DEVELOPER:

• Design and implement relational database structures optimized for performance and scalability.
• Develop and maintain complex SQL queries, stored procedures, triggers, and functions.
• Optimize database performance through indexing, query tuning, and regular maintenance.
• Ensure data integrity, consistency, and security across multiple environments.
• Collaborate with cross-functional teams to integrate SQL databases with applications and reporting tools.
• Develop and manage ETL (Extract, Transform, Load) processes for data ingestion and transformation.
• Monitor and troubleshoot database performance issues.
• Automate routine database tasks using scripts and tools.
• Document database architecture, processes, and procedures for future reference.
• Stay updated with the latest SQL best practices and database technologies.Data Retrieval: SQL Developers must be able to query large and complex databases to extract relevant data for analysis or reporting.
• Data Transformation: They often clean, join, and reshape data using SQL to prepare it for downstream processes like analytics or machine learning.
• Performance Optimization: Writing queries that run efficiently is key, especially when dealing with big data or real-time systems.
• Understanding of Database Schemas: Knowing how tables relate and how to navigate normalized or denormalized structures is essential.

QE:

• Design, develop, and execute test plans and test cases for data pipelines, ETL processes, and data platforms.
• Validate data quality, integrity, and consistency across various data sources and destinations.
• Automate data validation and testing using tools such as PyTest, Great Expectations, or custom Python/SQL scripts.
• Collaborate with data engineers, analysts, and product managers to understand data requirements and ensure test coverage.
• Monitor data pipelines and proactively identify data quality issues or anomalies.
• Contribute to the development of data quality frameworks and best practices.
• Participate in code reviews and provide feedback on data quality and testability.
• Strong SQL skills and experience with large-scale data sets.
• Proficiency in Python or another scripting language for test automation.
• Experience with data testing tools 
• Familiarity with cloud platforms and data warehousing solutions