Senior Software Engineer (Data Platform)
- San Francisco, United States
- Senior Level
- Posted
Skills
Required
- BigQuery
- Astronomer / Apache Beam / Terraform / Spacelift / Datadog / dbt / Spark / Dataproc
- ML / AI workloads
- event-driven / streaming data infrastructure
- message broker
- managed event bus
- stream processing system
- delivery guarantees
- Python
- Dataflow
- GKE
- Cloud Storage
Preferred
- Airflow
- cloud infrastructure
- infrastructure as code
- containers
- Kubernetes
- CI/CD
- access controls
- production observability
- DAGs
Join Handshake, a rapidly growing career marketplace and AI product company. As a Senior Data Platform Engineer, you will build and operate the infrastructure that moves data reliably across our platform. You will lead the technical direction for our workflow orchestration platform, data ingestion, data pipelines, and data warehouse. This is a hands-on technical leadership role with the opportunity to shape Handshake's data infrastructure strategy.
Concevoir et diriger la stratégie d'infrastructure de données de Handshake, y compris la plateforme d'orchestration des flux de travail (Airflow), l'ingestion de données, les pipelines de données, l'entrepôt de données (BigQuery) et l'infrastructure de données en streaming.
Diriger la direction technique et la feuille de route de notre plateforme Airflow et Astronomer tout en possédant ses opérations de production.
About Handshake
Collaborer étroitement avec les ingénieurs en apprentissage automatique, les scientifiques des données et d'autres ingénieurs pour maximiser la vitesse de la plateforme de données.
Responsibilities
- Experience with cloud infrastructure and infrastructure as code; comfortable working with containers, Kubernetes, CI/CD, access controls, and production observability
- Deep hands-on Airflow experience beyond writing DAGs: scheduling and execution behavior, deployment, scaling, upgrades, monitoring, and debugging failures
- A track record of leading ambiguous infrastructure initiatives: setting technical direction, making pragmatic architecture tradeoffs, and driving adoption across teams
Requirements
- Clear communication and a track record of partnering across teams while owning systems through production support
- Experience with event-driven or streaming data infrastructure, including a message broker or managed event bus and a stream processing system
- Sound understanding of CDC, delivery guarantees, idempotency, ordering, schema evolution, and recovery or replay in production pipelines
- Strong software engineering skills in Python and experience building and operating production data or distributed systems
- GCP services such as Pub/Sub, Dataflow, Datastream, BigQuery, GKE, and Cloud Storage
- Astronomer, Apache Beam, Terraform, Spacelift, Datadog, dbt, Spark or Dataproc
- Experience supporting ML or AI workloads such as inference pipelines, reproducible evaluations, or governed data access
- Supporting both batch and low-latency consumers, including product-facing data services or ML features
Pay
USD 166,000 - 207,000
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