Saturday to Wednesday
-
Transportation -Loan -Bonus -Military Service Option -Health insurance
-Game room
-In-house Medical doctor
-Occasional packages and gifts
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1001 - 5000 employees
Internet Provider / E-commerce / Online Services
توضیحات بیشتر
key Requirements
3 years experience in similar position Linux - Intermediate
Apache Kafka - Intermediate
Redis - Intermediate
Docker - Basic
Kubernetes - Intermediate
Grafana - Intermediate
Apache Airflow - Intermediate
Job Description
About the Role
Ripple is our centralized Customer Data Platform (CDP) and event-tracking engine at Tapsi. It serves as the backbone for Tapsi Group and its subsidiaries, powering high-throughput event ingestion, marketing automation triggers, and near-real-time analytical query serving at scale.
As a Data Engineer (Mid-Level) on the Growth Engine team, you will contribute to the design, development, and operation of our distributed streaming, storage, and lakehouse infrastructure. You will work on high-throughput pipelines, data processing systems, and cluster operations that support event ingestion, data quality, and analytical workloads across the group.
Responsibilities
Ripple is our centralized Customer Data Platform (CDP) and event-tracking engine at Tapsi. It serves as the backbone for Tapsi Group and its subsidiaries, powering high-throughput event ingestion, marketing automation triggers, and near-real-time analytical query serving at scale.
As a Data Engineer (Mid-Level) on the Growth Engine team, you will contribute to the design, development, and operation of our distributed streaming, storage, and lakehouse infrastructure. You will work on high-throughput pipelines, data processing systems, and cluster operations that support event ingestion, data quality, and analytical workloads across the group.
Responsibilities
- Data Infrastructure & Operations: Help deploy and operate robust data infrastructure across environments, including tools such as Kafka, StarRocks, Iceberg, and Airflow on Kubernetes.
- Lakehouse & Data Warehouse Architecture: Contribute to building and optimizing our lakehouse footprint using technologies such as Apache Iceberg, HDFS/Object Storage, and StarRocks or similar OLAP systems.
- Workflow Orchestration & Batch Pipelines: Design, implement, and maintain reliable batch and maintenance pipelines using Apache Airflow.
- Stream Processing & Ingestion: Build and maintain low-latency streaming services in Go, Kotlin, or Java that consume from Kafka and feed downstream systems.
- Schema Governance & Data Quality: Work with schema-registry pipelines such as Avro/Protobuf, validation rules, and dead-letter queue handling.
- Cross-Cluster Routing & Replication: Support event routing and replication workflows across clusters and environments.
- Performance Tuning & Observability: Help monitor and tune data pipelines and systems using Prometheus, Grafana, and OpenTelemetry.
- Technical Collaboration: Participate in RFCs, design discussions, and implementation reviews while following engineering best practices.
- Experience: 3+ years of experience in Data Engineering or distributed backend systems.
- Programming & Systems: Strong proficiency in Go, Kotlin, or Java, with a good understanding of concurrency and writing maintainable code.
- SQL & Database Expertise: Solid SQL skills, including joins, CTEs, and window functions, plus experience with RDBMS systems such as PostgreSQL or MySQL.
- Distributed Streaming: Hands-on experience with Kafka or similar distributed streaming platforms.
- Lakehouse & Modern Storage: Familiarity with data lakehouse or warehouse technologies such as Apache Iceberg, HDFS, StarRocks, ClickHouse, or Druid.
- Workflow Orchestration: Experience developing or debugging workflows in Apache Airflow.
- Infrastructure & Cluster Ops: Working knowledge of Kubernetes, Helm, and Linux environments.
- Data Modeling & Schemas: Familiarity with Avro or Protobuf and the basics of schema evolution and event-driven modeling.
- Spark & Flink: Familiarity with Apache Spark and Apache Flink for batch and stream processing.
- Mindset: Strong ownership, curiosity, and a practical approach to reliability and performance.
- Experience with CDP or marketing automation pipelines.
- Familiarity with BI/visualization tools such as Apache Superset.
- Exposure to GitOps workflows such as ArgoCD or Flux.
- Experience with Terraform or other infrastructure provisioning tools.
Job Requirements
Gender
Men / Women
Software
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