Kyiv
Our client is looking for an experienced Data Engineer to join a team responsible for building and operating a large-scale data platform that supports analytics, product capabilities, and business-critical data services.
The platform handles more than 150 billion events every day and stores petabytes of historical data. Beyond maintaining a traditional data lake, the team is responsible for data infrastructure, ingestion frameworks, schema management, processing pipelines, and storage interfaces.
This role is ideal for engineers who enjoy working with distributed systems, taking ownership of production environments, and solving challenges at massive scale.
Key technologies include:
- Processing and streaming: Spark, Kafka
- Data lake and formats: S3, Parquet, Delta Lake, Iceberg, Hadoop, Hive
- Cloud and compute:** AWS, EMR/EMR Serverless, Athena
- Analytics and data platforms:** BigQuery, BigLake, Aerospike, AWS Glue, Databricks Delta Engine
- Languages: Scala, Python (team focus), plus a broader polyglot engineering environment
Responsibilities:
- Design and develop scalable data pipelines, from ingestion through transformation and delivery.
- Build and maintain Spark-based processing solutions for both batch and streaming workloads.
- Ensure reliability, scalability, and performance of production data systems.
- Work closely with engineering teams, product stakeholders, and platform owners to deliver robust data solutions.
- Contribute to technical standards, best practices, and operational excellence within the team.
- Participate in supporting and improving large-scale distributed systems running in production.
Requirements:
- 3+ years of software engineering experience.
- Strong hands-on experience with Scala and/or Java.
- Solid understanding of Java fundamentals.
- Production experience with Spark and Kafka.
- Experience working with Hadoop-related technologies and distributed data platforms.
- Hands-on experience with cloud environments such as AWS, GCP, Azure, CDP, MapR, or similar.
- Practical experience with AWS services, particularly S3 and EMR/EMR Serverless.
- Experience designing, building, and maintaining distributed cloud-based systems.
- Strong analytical thinking and communication skills.
- Professional level of English.
Nice to Have:
- Additional experience with Scala development.
- Familiarity with cloud security, authentication, and authorization concepts in AWS.
- Experience with CI/CD practices and tooling.
- Knowledge of Infrastructure as Code solutions such as Terraform.
- Previous experience in a SaaS product environment.
Benefits
- Unlimited paid vacation policy plus public holidays.
- Medical insurance and paid sick leave.
- Sports and meal allowance.
- Complimentary snacks, breakfast, fruit, and beverages in the office.
- Parking reimbursement.
- Team events, company gatherings, and social activities.
- Modern equipment package including a MacBook and dual-monitor setup.
Why Join
You will become part of a team operating data systems at an exceptional scale, working with petabytes of data and hundreds of billions of events every day. The role offers exposure to complex distributed architectures, real-time data processing, cloud infrastructure, and platform engineering.
This is an opportunity to work at the intersection of Software Engineering, Data Engineering, and DevOps while contributing to the evolution of a rapidly growing data platform and solving large-scale technical challenges.