AWS Data Engineer (Redshift)

Location: Hyderabad | Work From Office

Experience: 48 Years

Notice Period: Immediate to 30 Days preferred

We are looking for an experienced AWS Data Engineer with strong hands-on experience in Amazon Redshift, AWS Glue, S3, SQL and PySpark to design and build scalable data pipelines and cloud data warehouse solutions.

Key Responsibilities

- Design, develop and maintain ETL/ELT pipelines using AWS services.
- Build and optimize data pipelines using AWS Glue, S3 and PySpark.
- Develop and maintain Amazon Redshift data warehouse solutions.
- Load and transform data from S3 and various source systems into Redshift.
- Write complex and optimized SQL queries, stored procedures and data transformations.
- Design appropriate Redshift distribution keys and sort keys.
- Perform Redshift query and workload optimization, including identifying data skew, inefficient joins and unnecessary data scans.
- Implement incremental loads, CDC and data-quality checks.
- Work with Redshift Spectrum for querying data directly from S3 where appropriate.
- Implement data partitioning and file-format optimization, preferably using Parquet.
- Develop scalable PySpark transformations for large datasets.
- Implement monitoring, logging and failure/retry mechanisms for production pipelines.
- Work with IAM, CloudWatch, Lambda/EventBridge and other AWS services as required.




- Participate in CI/CD and deployment automation for data pipelines.
- Troubleshoot production data pipeline and Redshift performance issues.

Required Skills

Mandatory:

- 48 years of Data Engineering experience.
- Strong hands-on experience with Amazon Redshift.
- Strong SQL skills.
- Hands-on experience with AWS Glue.
- Strong experience with Amazon S3.
- Experience with PySpark / Apache Spark.
- Strong understanding of ETL/ELT architecture.
- Experience with incremental loading and data-quality validation.
- Good understanding of cloud data warehouse concepts.

Redshift-specific expertise:

- COPY command and S3-to-Redshift loading.
- DISTKEY / SORTKEY selection.
- Distribution styles.
- Query optimization.
- Data skew.
- VACUUM / ANALYZE concepts.
- Redshift Spectrum.
- Workload management.
- Large-volume data loading and optimization.

Valuable to Have:

- AWS Lambda
- EventBridge
- CloudWatch
- Athena
- EMR
- IAM
- Airflow / MWAA
- dbt
- Terraform
- CI/CD
- Python

Ideal Candidate We are looking for someone who has genuine hands-on Redshift experience, not just Redshift listed in the resume. The candidate should be able to explain a complete architecture such as:

Source Systems S3 AWS Glue/PySpark Redshift BI/Analytics and confidently troubleshoot Redshift performance, data loading, distribution, sorting and SQL optimization.

📌 Aws Data Engineer (Hyderabad)
🏢 Paltech Consulting
📍 Hyderabad