Amazon Redshift Developer

Job Description

We are seeking an experienced Amazon Redshift Developer / Data Engineer to design, develop, and optimize cloud-based data warehousing solutions. The ideal candidate should have expertise in Amazon Redshift, ETL processes, SQL optimization, and cloud-based data lake architectures. This role involves working with large-scale datasets, performance tuning, and building scalable data pipelines. Key Responsibilities: Design, develop, and maintain data models, schemas, and stored procedures in Amazon Redshift. Optimize Redshift performance using distribution styles, sort keys, and compression techniques. Build and maintain ETL/ELT data pipelines using AWS Glue, AWS Lambda, Apache Airflow, and dbt. Develop complex SQL queries, stored procedures, and materialized views for data transformations. Integrate Redshift with AWS services such as S3, Athena, Glue, Kinesis, and DynamoDB. Implement data partitioning, clustering, and query tuning strategies for optimal performance. Ensure data security, governance, and compliance (GDPR, HIPAA, CCPA, etc.). Work with data scientists and analysts to support BI tools like QuickSight, Tableau, and Power BI. Monitor Redshift clusters, troubleshoot performance issues, and implement cost-saving strategies. Automate data ingestion, transformations, and warehouse maintenance tasks. Required Skills & Qualifications: 6+ years of experience in data warehousing, ETL, and data engineering. Strong hands-on experience with Amazon Redshift and AWS data services. Expertise in SQL performance tuning, indexing, and query optimization. Experience with ETL/ELT tools like AWS Glue, Apache Airflow, dbt, or Talend. Knowledge of big data processing frameworks (Spark, EMR, Presto, Athena). Familiarity with data lake architectures and modern data stack. Proficiency in Python, Shell scripting, or PySpark for automation. Experience working in Agile/DevOps environments with CI/CD pipelines.