Role & responsibilities
Design, develop, and maintain scalable data pipelines and data processing solutions.
Build and optimize data solutions using Snowflake and dbt.
Work extensively with AWS services, including S3, MWAA, MSK, and SageMaker.
Develop large-scale data processing solutions using Hadoop, Hive, Spark, and PySpark.
Build and manage data ingestion and streaming pipelines using Kafka/MSK.
Develop and orchestrate workflows using Apache Airflow/AWS MWAA.
Write and optimize complex queries using Advanced SQL.
Develop data processing and automation solutions using Python and, where applicable, Scala.
Work with up-to-date data architectures and table/storage formats such as Apache Iceberg.
Develop and maintain configuration and deployment components using YAML, Git, and Docker.




Troubleshoot data pipeline issues and improve performance, scalability, and reliability.
Collaborate with data, analytics, cloud, and business teams to deliver data engineering solutions.

Preferred candidate profile
Robust hands-on experience with AWS
Strong experience with Snowflake
Experience with Hadoop/Big Data ecosystem
Strong hands-on experience in Spark and/or PySpark
Strong Python and SQL
Experience developing and maintaining ETL/ELT data pipelines
Positive understanding of large-scale and distributed data processing

📌 Senior Data Engineer Bengaluru
🏢 Allegis Group
📍 Bengaluru