Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Mid-level role, metro Hyderabad, strong employer brand, and broad Databricks/AWS skillset increase candidate competition.
Core data engineering skills (AWS, Spark, Databricks) are highly transferable across industries.
Explicit 3-5 years requirement plus mandatory AWS, Databricks, PySpark and production experience increases filter strictness.
Develop and support AWS cloud-native data lakes and data ecosystems using services like Glue Studio, Athena, Redshift, and PostgreSQL.
Build and optimize scalable data pipelines in Databricks using PySpark/SQL, including cluster and job configuration and performance tuning.
Work within an onshore-offshore delivery model and contribute to improving team processes and knowledge sharing.
3-5 years of IT experience with AWS cloud-native data lake development and production support.
Strong programming skills in Python, Spark, and experience with AWS services such as Glue Studio, Athena, Redshift, PostgreSQL/MySQL.
At least 1-2 years experience working in an onshore-offshore delivery model.
Experience with Databricks Lakehouse architecture, Delta Lake, Unity Catalog, Databricks Workflows, and data security/privacy best practices.
Demonstrates strong cloud engineering skills with hands-on experience in Databricks and AWS data services in complex global environments.
Experienced in production-grade data pipeline development and optimization with a focus on performance tuning and scalability.
Has functional knowledge or prior experience in Enterprise Functions and excels in improving team processes and collaboration across global delivery models.