Senior Big Data Engineer (Databricks + AWS)

Senior Big Data Engineer (Databricks + AWS) Job | Data | SoftServe | Remote | No Fluff Jobs.

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– Senior
– Remote
– Offer valid until: 01.11.2026 (30 days left)
Must have
– Python
– AWS
– Databricks
– English
Requirements description
– 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
Your responsibilities
1. Design, develop, and maintain scalable batch and streaming data pipelines
2. Build and optimize data processing solutions using Python (PySpark) and SQL
3. Develop and manage data workflows using Databricks on AWS
4. Work with Apache Spark and Databricks for large-scale data processing
5. Implement and maintain Delta Lake-based data architectures
6. Utilize orchestration tools such as Apache Airflow or MWAA to manage workflows
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Offer description
ABOUT THE ROLE
IIn 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.
Job details
– Online recruitment
– Start ASAP
– Fully remote
Perks in the office
– Free coffee
– Canteen
– Bike parking
– Free snacks
– Free parking
– In-house trainings
– Modern office
– No dress code
Benefits
– Sport subscription
– Training budget
– Private healthcare
– International projects
– Flat structure
– Small teams