Job Summary:
We are looking for a Data Warehouse Developer with strong expertise in SQL and a deep understanding of Data Warehouse (DWH) concepts. The role involves designing, developing, and optimizing SQL queries for data extraction, transformation, and reporting within large-scale data warehouse environments. The ideal candidate will translate business needs into efficient SQL queries and data models to support analytics and decision-making.
Key Responsibilities:
- Develop complex SQL queries for data extraction, transformation, and loading (ETL) processes within the data warehouse—Document SQL development standards and procedures.
- Design and optimize SQL scripts to improve data retrieval performance and data quality.
- Implement and maintain dimensional data models (star schema, snowflake schema) using SQL.
- Write stored procedures, functions, views, and triggers to automate data workflows.
- Collaborate with BI teams and business stakeholders to gather reporting requirements and translate them into SQL-based solutions. Optimize existing SQL queries and database objects for better performance. Work with large datasets to validate and ensure data accuracy and consistency.
- Perform data profiling and data cleansing using SQL to ensure high-quality data in the warehouse.
- Troubleshoot and debug SQL code related to data warehousing processes.
- Manage Slowly Changing Dimensions (SCD) to accurately track historical data changes over time.
- Ensure data quality and consistency by implementing validation rules and data cleansing procedures within the data warehouse. Develop and maintain metadata and documentation for data warehouse architecture, schemas, and ETL processes.
Must Have Skills:
- Strong SQL skills: complex queries, joins, stored procedures, views, and performance tuning.
- Solid understanding of Data Warehouse concepts: fact/dimension tables, slowly changing dimensions (SCD), schema design.
- Experience with AWS data services, including but not limited to:
- Amazon Redshift (managed data warehouse)
- AWS Glue (ETL service)
- Amazon S3 (data lake/storage)
- AWS Lambda (serverless compute for ETL automation)
- Amazon RDS/Aurora (relational databases)
- Familiarity with cloud architecture and security best practices on AWS.
- Experience with ETL development and orchestration in AWS environments.
- Ability to optimize data workflows and SQL queries for performance and cost-efficiency on AWS
Good to Have Skills:
- Design and develop dimensional and normalized data models (star schema, snowflake schema) to efficiently support analytical queries.
- Understand the differences between OLTP and OLAP systems and design solutions tailored for analytical workloads. Collaborate with business analysts and data consumers to gather requirements and translate them into data warehouse design and reporting solutions.
- Apply data governance and security best practices to protect sensitive data within the warehouse.
- Use SQL extensively for data extraction, transformation, and analysis in the data warehouse
Key Skills - AWS Solutions Architecture, Omnia Platform Knowledge, Vector Db, RDBMS with ANSI SQL
Assist in data collection and processing, Support data pipeline development, Document data engineering processes, Perform basic data analysis, Collaborate with senior data engineers.
Bachelor's/Master's in Engineering 3-5 years