About this role

Senior Big Data Engineer (Databricks + AWS) SoftServe Daily tasks: - Design, develop, and maintain scalable batch and streaming data pipelines - Build and optimize data processing solutions using Python (PySpark) and SQL - Develop and manage data workflows using Databricks on AWS - Work with Apache Spark and Databricks for large-scale data processing - Implement and maintain Delta Lake-based data architectures - Utilize orchestration tools such as Apache Airflow or MWAA to manage workflows - Support implementation of streaming solutions using Apache Kafka, Amazon MSK, or Kinesis - Collaborate with technical and business stakeholders to deliver effective data solutions - Participate in architecture discussions and contribute to continuous improvement initiatives within the team - Participate in the full project lifecycle, from PoC and MVP stages to production implementation Musts: Python, AWS, Databricks 4+ years of experience in Big Data or Data Engineering Strong proficiency in Python (PySpark) and SQL Hands-on experience with AWS cloud services for data engineering solutions Practical experience with Databricks on AWS , including building and managing data pipelines Strong knowledge of Apache Spark and large-scale data processing Experience with batch and streaming data processing Familiarity with Delta Lake and Databricks components such as Workflows and Jobs Experience with orchestration tools such as Apache Airflow or MWAA Knowledge of streaming technologies such as Apache Kafka, Amazon MSK, or Kinesis Upper-intermediate or higher level of English ABOUT THE ROLE I In this role, you will contribute to developing scalable cloud-based data solutions on AWS using Databricks and modern big data technologies.

You will work on batch and streaming data pipelines, support optimisation and modernisation initiatives, and collaborate with cross-functional teams to deliver reliable and efficient data platforms across different stages of the project lifecycle.

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