The Senior Data Engineer will design and implement scalable data systems, focusing on AWS-based architectures, data pipelines, and performance tuning, while mentoring other engineers.
Description
We are building a greenfield analytics platform supporting both batch and real-time data processing. We are looking for a Senior Data Engineer who can design, implement, and evolve scalable data systems in AWS.
This role combines hands-on development, architectural decision-making, and platform ownership.
Core Responsibilities:
- Design and implement batch and streaming data pipelines using Apache Spark.
- Build and evolve a scalable AWS-based data lake architecture.
- Develop and maintain real-time data processing systems (event-driven pipelines).
- Own performance tuning and cost optimization of Spark workloads.
- Define best practices for data modeling, partitioning, and schema evolution.
- Implement monitoring, observability, and data quality controls.
- Contribute to infrastructure automation and CI/CD for data workflows.
- Participate in architectural decisions and mentor other engineers.
Required Qualifications:
- 5+ years of experience in Data Engineering.
- Strong hands-on experience with Apache Spark (including Structured Streaming).
- Experience building both batch and streaming pipelines in production environments.
- Proven experience designing AWS-based data lake architectures: S3, EMR, Glue, Athena.
- Experience with event streaming platforms such as Apache Kafka or Amazon Kinesis.
- Experience implementing lakehouse formats such as Delta Lake.
- Strong understanding of partitioning strategies and schema evolution.
- Experience using SparkUI and AWS CloudWatch for profiling and optimization.
- Strong understanding of Spark performance tuning (shuffle, skew, memory, partitioning).
- Proven track record of cost optimization in AWS environments.
- Experience with Docker and CI/CD pipelines.
- Experience with Infrastructure as Code: Terraform, AWS CDK.
- Familiarity with monitoring and observability practices.
- Experience in the Financial domain.
- Experience running Spark workloads on Kubernetes.
- Experience implementing data quality frameworks or metadata/lineage systems.
- English - B2, Ukrainian- Native MUST
Top Skills
Amazon Kinesis
Apache Kafka
Spark
Athena
AWS
Aws Cdk
Aws Cloudwatch
Ci/Cd
Delta Lake
Docker
Emr
Glue
S3
Sparkui
Terraform
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