Data Warehouse Developer

Data Warehouse Developer

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.