Associate Data Engineer

Key Responsibilities:

• Develop complex SQL queries for data extraction, transformation, and loading (ETL) processes within the data
• warehouseDocument 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