Data Engineer (Mid/Senior)
Tasks
- Build and operate data platform end to end
- Build ingestion from BigQuery Elasticsearch third party APIs
- Design high volume ingestion into ClickHouse
- Develop data pipelines and data modeling
- Ensure data quality and reliability
- Implement observability and monitoring
- Integrate Kafka and streaming ingestion
- Integrate authentication pagination rate limiting retries error handling
- Maintain Lakehouse architecture
- Manage pipeline deduplication and idempotency
- Optimize ClickHouse performance
- Perform platform operations and reliability tasks
- Process data in batches and real time
- Troubleshoot production data workloads
Perks/Benefits
- Flexible working hours
- Meal allowance
- Multisport PassSport Subsidy
- Paid sick leave
- Private health insurance
- Professional development
- Remote work option
- Technical community involvement
- Transportation allowance
- Workshops and meetups
Skills/Tech-stack
Amazon EKS | Amazon S3 | Apache Iceberg | Authentication | Backpressure management | BigQuery | Change Data Capture | ClickHouse | Cloud Storage | DBT | Data Capture | Data Modeling | Data Quality | Deduplication | Embedding Infrastructure | Error Handling | GenAI | Google Cloud | Google Cloud Storage | Idempotency | Kafka | Kafka Schema Registry | Kubernetes | LLM | Materialized views | Monitoring | Node.js | Observability | Pagination | Parquet | Primary Key | Production ML | Python | RAG | Rate Limiting | Retries | Schema Registry | Sorting Key | Storage Engines | TypeScript | Vector Databases
Education
N/A
Roles
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