Job highlights

- Experienced Data Engineer with expertise in AWS, PySpark, Python, Databricks, and Lakehouse architecture

- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows; optimize Spark jobs; implement data quality and security measures; collaborate with stakeholders

We are looking for an experienced Data Engineer with robust hands-on expertise in AWS, PySpark, Python, and Databricks. The ideal candidate should have experience in designing, developing, and maintaining scalable data pipelines, implementing data processing solutions, and building robust ETL/ELT workflows on cloud platforms.

Roles & Responsibilities

- Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks.

- Develop and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data.

- Work extensively with AWS services such as S3, Glue, Lambda, EMR,



Redshift, and Athena.

- Develop data transformation and processing logic using PySpark and Python.

- Build and manage data engineering solutions using Databricks.

- Work with Delta Lake, Delta Tables, and Lakehouse architecture.

- Implement data ingestion, cleansing, transformation, and aggregation processes.

- Optimize Spark jobs and troubleshoot performance issues.

- Implement data quality checks, error handling, and monitoring mechanisms.

- Collaborate with data architects, data analysts, and business stakeholders.

- Ensure data security, governance, and compliance across data pipelines.

- Participate in code reviews, technical discussions, and deployment activities

📌 Excellent Opportunity For Data Engineers (Hyderabad)
🏢 Nous Info Solution
📍 Hyderabad