Job Title

Important Note: Please apply only if you have relevant experience for the role. Submitting applications for positions unrelated to your skills or experience may result in your profile being flagged by . This could reduce your visibility for future job postings and recruiters in your area of expertise. Key Responsibilities: Design and manage scalable Redshift data warehouses for analytical workloads. Implement and maintain Star Schema-based dimensional models to support data marts and business reporting. Develop complex SQL queries and scripts for data transformation, aggregation, and cleansing. Optimize Redshift clusters, queries, and data distribution strategies for performance and cost. Integrate data from multiple sources (including S3, Postgres, APIs, and third-party feeds) into Redshift using ETL/ELT tools. Collaborate with Data Architects and Modelers to ensure data models are efficient, scalable, and align with business requirements. Ensure data integrity, availability, security, and governance across the Redshift environment. Monitor system performance, perform tuning , and troubleshoot operational issues . Participate in Agile/Scrum ceremonies and work collaboratively with cross-functional teams. Required Qualifications: 5+ years of experience in data engineering or warehousing with a focus on Amazon Redshift . Strong proficiency in SQL , with ability to write and optimize complex queries for large datasets. Solid understanding of dimensional modeling , Star Schema , and OLAP vs OLTP data structures. Experience in designing analytical data marts and transforming raw/transactional data into structured analytical formats. Hands-on experience with ETL tools (e.g., AWS Glue). Familiarity with Amazon Redshift Spectrum , RA3 nodes , and data distribution/sort keys best practices. Comfortable working in cloud-native environments, particularly AWS (S3, Lambda, CloudWatch, IAM, etc.). Preferred Qualifications: Exposure to data lake integration , external tables , and Redshift-Unload/Copy operations. Experience in BI tools (e.g., Tableau, Quick Sight) to validate and test data integration. Familiarity with Python or PySpark for data transformation scripting. Understanding of CI/CD for data pipelines and version control using Git. Knowledge of data security, encryption, and compliance in a cloud environment. Minimum Qualification: 15 years of full-time education If you are Interested in the above opportunity and having the experience as required . kindly share your updated resume to immediately with the details below (Mandatory) Name: Contact No. Email id: Skillset: Total exp: Relevant Exp: Fulltime highest qualification (Year of completion with College and University Name ): Current organization details (Payroll company): Current CTC: Expected CTC: Notice period: Current location: Preferred Location: Any gaps between your education or career (If yes pls specify the duration): Will you be able to join within 30/45 days? (Yes/NO)