Redshift Engineer

AWS Redshift Lead

Role: AWS Redshift Lead
Exp: 8-10 Yrs
Location: All India Infosys Location
Work Mode: 5 days WFO
Interview: Virtual

Key Responsibilities:

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Design and manage scalable Redshift data warehouses for analytical workloads.

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Implement and maintain Star Schema-based dimensional models to support data marts and business reporting.

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Develop complex SQL queries and scripts for data transformation aggregation and cleansing.

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Optimize Redshift clusters queries and data distribution strategies for performance and cost.

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Integrate data from multiple sources (including S3 Postgres APIs and third-party feeds) into Redshift using ETL/ELT tools.

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Collaborate with Data Architects and Modelers to ensure data models are efficient scalable and align with business requirements.

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Ensure data integrity availability security and governance across the Redshift environment.

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Monitor system performance perform tuning and troubleshoot operational issues.

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Participate in Agile/Scrum ceremonies and work collaboratively with cross-functional teams.

Required Qualifications:

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5 years of experience in data engineering or warehousing with a focus on Amazon Redshift.

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Strong proficiency in SQL with ability to write and optimize complex queries for large datasets.

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Solid understanding of dimensional modeling Star Schema and OLAP vs OLTP data structures.

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Experience in designing analytical data marts and transforming raw/transactional data into structured analytical formats.

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Hands-on experience with ETL tools (e.g. AWS Glue).

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Familiarity with Amazon Redshift Spectrum RA3 nodes and data distribution/sort keys best practices.

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Comfortable working in cloud-native environments particularly AWS (S3 Lambda CloudWatch IAM etc.).

Preferred Qualifications:

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Exposure to data lake integration external tables and Redshift-Unload/Copy operations.

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Experience in BI tools (e.g. Tableau QuickSight) to validate and test data integration.

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Familiarity with Python or PySpark for data transformation scripting.

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Understanding of CI/CD for data pipelines and version control using Git.

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Knowledge of data security encryption and compliance in a cloud environment.