Description :

We are seeking a highly skilled AWS Redshift Data Engineer to design, develop, and maintain our large-scale data warehousing solutions.

In this role, you will be the architect of our data pipelines, ensuring that massive datasets are ingested, transformed, and optimized for high-performance analytics.

You will work at the intersection of data engineering and cloud architecture to provide our business intelligence teams with the foundation they need for data-driven decision-making.

Core Responsibilities :

- Warehouse Architecture : Design and implement scalable data warehouse models using Amazon Redshift (including RA3 nodes and Redshift Spectrum).

- ETL/ELT Development : Build and automate robust data pipelines to migrate data from diverse sources (S3, Aurora, DynamoDB, external APIs) into Redshift.

- Performance Tuning : Optimize query performance by managing distribution keys, sort keys, and compression encodings.

- Perform regular VACUUM and ANALYZE operations and monitor WLM (Workload Management) queues.

- Data Modeling : Create and maintain complex schemas, star/snowflake schemas, and materialized views to support BI reporting tools (e.g., Tableau, QuickSight).

- Automation & Monitoring : Develop infrastructure as code (Terraform/CloudFormation) and monitor cluster health using CloudWatch and Redshift Advisor.

Technical Skills & Qualifications :

1. Deep AWS Expertise :

- Primary : Amazon Redshift (Provisioned & Serverless), S3, Glue (ETL & Data Catalog), and AWS Lambda.

- Secondary : Amazon Kinesis (for streaming data), Athena, and IAM policy management.

2. Data Engineering & Languages :

- SQL Mastery : Advanced SQL writing skills, including window functions, complex joins, and stored procedures specifically optimized for OLAP databases.

- Programming : Proficiency in Python (specifically libraries like Pandas, Boto3, and PySpark).

- Orchestration : Experience with Apache Airflow or AWS Step Functions to manage complex workflow dependencies.

3. Database Optimization :

- Expertise in Redshift-specific architecture :

a. Distribution Styles(Even, Key, All, Auto).

- Sorting : Compound and Interleaved sort keys.

- Data Shares : Implementing cross-account data sharing.

4. DevOps & Methodology :

- Experience with Git-based version control and CI/CD pipelines.

- Knowledge of Data Lakehouse architecture (integrating S3 data lakes with Redshift).

Preferred Qualifications :

- AWS Certified Data Engineer Associate or AWS Certified Data Analytics Specialty.

- Experience with dbt (data build tool) for in-warehouse transformations.

- Familiarity with migration projects (e.g., moving from on-premise SQL Server/Oracle to Redshift)