Data Warehouse Developer

Job Description

The Data Warehouse Developer will be responsible for the design, development, maintenance, and optimization of our enterprise data warehouse and ETL (Extract, Transform, Load) processes. This role involves working closely with business users, data analysts, and other IT teams to understand data requirements, build efficient data pipelines, and ensure the integrity and availability of data for reporting and analytical purposes. The ideal candidate will have strong expertise in SQL, ETL tools, data modeling, and a passion for building robust data solutions. Responsibilities Data Warehouse Design & Development: Design, develop, and maintain data warehouse schemata (star schema, snowflake schema, 3NF) based on business requirements. Create and manage database objects such as tables, views, indexes, stored procedures, and functions within the data warehouse. Optimize data warehouse performance through efficient indexing, partitioning, and query tuning. ETL Development & Management: Develop, test, and deploy robust and scalable ETL processes to extract data from various source systems (relational databases, flat files, APIs, cloud sources). Transform raw data into a clean, consistent, and structured format suitable for the data warehouse. Load transformed data into the data warehouse using various ETL tools/techniques ([mention specific tools like SSIS, Informatica, Talend, Azure Data Factory, AWS Glue, Python scripts, etc.]). Monitor, troubleshoot, and optimize existing ETL jobs for performance and reliability. Data Modeling: Collaborate with business analysts and stakeholders to understand data needs and translate them into logical and physical data models for the data warehouse. Ensure data models support reporting, analytics, and business intelligence requirements. Data Quality & Governance: Implement data quality checks and validation rules within ETL processes to ensure data accuracy and integrity. Assist in establishing data governance policies and procedures for the data warehouse. Performance Tuning & Optimization: Analyze and optimize complex SQL queries for performance efficiency within the data warehouse environment. Identify and resolve performance bottlenecks in ETL processes and database queries. Documentation & Support: Create and maintain comprehensive documentation for data warehouse architecture, ETL processes, data models, and data definitions. Provide technical support and guidance to data analysts and end-users regarding data access and interpretation. Collaboration: Work closely with data engineers, BI developers, and reporting teams to deliver end-to-end data solutions.