3 дня назад
Senior Data Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (Kafka/Flink/AWS): Building and operating a cloud-based data platform for high-volume sensor and telemetry data with an accent on real-time streaming, lakehouse architecture, and analytical serving layers. Focus on designing Kafka and Flink pipelines, migrating data platforms to AWS, deploying workloads on Kubernetes, and integrating ML and LLM capabilities.
Location: Bulgaria, Georgia, Lithuania, Mexico, Moldova, Poland, or Ukraine. Flexible work options include remote and hybrid opportunities.
Company
delivers technology services for a global data center provider building hyperscale and edge infrastructure across the Americas, EMEA, and Asia-Pacific.
What you will do
- Design, build, and operate high-throughput real-time streaming pipelines with Apache Kafka and Apache Flink.
- Define streaming data contracts, Avro schemas, and schema evolution through a schema registry.
- Build analytical serving layers with ClickHouse or similar OLAP databases and develop REST APIs for dashboards and downstream consumers.
- Develop batch and scheduled workflows with Apache Airflow, operate an Apache Iceberg lakehouse on Amazon S3, and use PySpark and Athena.
- Deploy data workloads on Amazon EKS using Kubernetes, Helm, Argo CD, GitOps, Terraform, and GitHub Actions.
- Monitor production platforms, troubleshoot incidents, maintain documentation, and migrate pipelines from Azure-based platforms to AWS.
Requirements
- 7+ years of experience in data or software engineering, including production streaming systems.
- Deep hands-on experience with Apache Kafka and Apache Flink or an equivalent stream-processing framework, including Java.
- Strong Python and SQL skills across transactional and analytical databases.
- Experience with Iceberg, Delta Lake, or Hudi; Parquet, Avro, schema registries, Athena, or Spark SQL.
- Production experience with analytical databases such as ClickHouse, Druid, or Pinot, plus SQL Server or PostgreSQL.
- Experience with AWS, Kubernetes, Amazon EKS, Helm, Argo CD, GitOps, Terraform, GitHub Actions, observability, and incident response.
Nice to have
- Knowledge of Azure Event Hubs, Data Factory, and Synapse.
- Experience with industrial telemetry, OPC UA, BMS/EPMS, or time-series sensor data.
- Experience with cloud migrations, data center operations, data quality frameworks, data contracts, or metadata management.
Culture & Benefits
- Technical and non-technical training, internal conferences, and meetups.
- Mentorship and professional development support.
- Health insurance and sports activities.
- Flexible remote and hybrid work options.
- Referral rewards, work anniversary benefits, and additional vacation days.
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