Job Summary

We are looking for an experienced AWS Databricks Engineer to design, develop, and optimize scalable data pipelines and data processing solutions on cloud platforms. The ideal candidate should have solid hands-on experience with Databricks, Spark, PySpark, SQL, and AWS services.

Job Details
Notice Period: Immediate Joiners Preferred

Responsibilities
Design and develop scalable data pipelines using Databricks and PySpark.
Build and maintain ETL/ELT workflows for large-scale data processing.
Work with AWS services such as S3, Glue, Redshift, EMR, and Lambda.
Develop and optimize SQL queries for large datasets.
Implement data warehousing and lakehouse architectures.
Collaborate with data engineers, analysts, and business teams to support analytics and reporting requirements.
Ensure data quality, performance optimization, and scalability of data pipelines.





Required Skills
Solid hands-on experience with Databricks, Apache Spark, and PySpark.
Advanced proficiency in SQL.
Experience building ETL / ELT pipelines.
Hands-on experience with AWS services (S3, Glue, Redshift, EMR, Lambda).
Experience with data warehousing and big data technologies.
Robust understanding of data pipeline architecture and performance optimization.

Nice to Have
Experience with Delta Lake / MLflow / Lakehouse architecture.
Exposure to Airflow, Kafka, or streaming data pipelines.
Experience working in cloud-based data platforms.

Education
Bachelors degree in Computer Science, Engineering, or related field.

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