Lead Data Engineer
Tasks
- Automate infrastructure and platform workflows
- Collaborate with product and infrastructure teams on scalable practices
- Define and maintain platform standards and guardrails
- Design and operate streaming systems
- Drive vendor agnostic data platform architecture
- Ensure data observability and data quality
- Operate data platform infrastructure on Kubernetes and cloud
- Own data platform ingestion
- Plan capacity and manage incident response
- Process and deliver batch and streaming data
- Separate ingestion storage compute and serving layers
- Support ML workloads feature store model retraining model deployment and monitoring
Perks/Benefits
- Commuting support
- Employee stock options
- Learning budget
- Onsite gym
- Private health insurance
- Referral program
- Snacks and drinks
- Work from anywhere
Skills/Tech-stack
AWS | Access Control | Apache Flink | Apache Iceberg | Apache Spark | Apache Spark Streaming | Batch Processing | Capacity Planning | Cloud platform | Cost Optimization | DBT | Data Engineering | Data Governance | Data Modeling | Data Quality | Data Security | Data platform | Distributed Systems | Event Driven | Event-driven architecture | Feature Store | GDPR | Go | Google Cloud | Google Cloud Platform | ISO 27001 | ISO 27701 | Incident Response | Infrastructure automation | Kafka | Kubernetes | MLOps | Machine Learning | Machine learning deployment | Metadata Management | Monitoring | Observability | Parquet | Partitioning | Python | Replay Strategy | Rust | SOC 2 | Scala | Schema evolution | Snowflake | Spark Streaming | Streaming processing
Education
N/A
Roles
Data Engineer | Engineer | Lead | Lead Data | Lead Data Engineer
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