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Senior Data Platform Engineer

🕒 4 days ago
PostgreSQLKafkaDebeziumKubernetes

📜 Description

  • Design and build platform services, tools, and workflows for contract-driven data publishing and consumption.
  • Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration.
  • Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code.
  • Build tooling that gives product engineers fast feedback before they publish or change data products.
  • Help define how Smartly models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution.
  • Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery.

🛠️ Requirements

  • Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments.
  • Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes.
  • Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance.
  • Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies.
  • Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows.
  • Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership.
  • Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems.

Benefits

  • Wellbeing support
  • Paid holidays
  • Family leave
  • Equity options
  • Career development opportunities
  • A flexible hybrid workplace that balances office collaboration with focused remote work. At Smartly we work 3 days a week from the office.
Anthropic

Data Infrastructure Engineer, Pre-training

Anthropic👥 10,000+ employees🏢 Research Services🤝 B2B
🕒 yesterday

Join the Pre-training team as a Staff Engineer to design and implement data processing infrastructure for large language model training, ensuring safety and reliability in AI systems.

Data Processing InfrastructureLarge Language ModelsDistributed SystemsApache Spark

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