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Handshake is a career platform serving 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, the company launched Handshake AI, a rapidly growing AI data business that has scaled from $0 to ~$1B run rate, paying ~$60M monthly to over 30K individuals.
You will join the Data and ML Platform team as a Senior Data Platform Engineer, owning the infrastructure that moves data reliably across Handshake's career marketplace and AI products. This is a hands-on technical leadership role where you will shape the company's data infrastructure strategy and set technical direction for workflow orchestration, data ingestion, data pipelines, data warehouse, and streaming infrastructure.
Key responsibilities include:
- Lead technical direction and roadmap for the Airflow/Astronomer platform while owning production operations: deployment, DAG packaging, scheduler and worker capacity, upgrades, observability, and incident response.
- Build paved paths for authoring, testing, deploying, and operating workflows, including reusable operators, CI checks, local and staging environments, and runbooks.
- Design and operate streaming and change data capture pipelines using Pub/Sub, Dataflow, Beam, and Datastream to serve analytics and product use cases.
- Make data delivery resilient to retries, duplicates, schema changes, late events, backfills, and replay; define latency, freshness, and reliability targets.
- Improve cloud foundation behind data workloads with Kubernetes, Terraform, IAM, secrets, CI/CD, and cost-aware capacity management.
- Lead cross-team design decisions on data contracts, interfaces, and operational ownership; mentor engineers and align application, analytics, ML, and cloud partners on scalable approaches.
- Participate in on-call, troubleshoot production failures, and turn incidents into durable improvements.
- Build dependable data and orchestration foundations for AI workloads, including batch inference, evaluation datasets, and agent-facing data.
You will collaborate closely with ML engineers, data scientists, and other engineers to maximize velocity on the data platform and support Handshake's growing AI development.
REQUIREMENTS:
- Strong software engineering skills in Python and experience building and operating production data or distributed systems.
- Deep hands-on Airflow experience beyond writing DAGs: scheduling and execution behavior, deployment, scaling, upgrades, monitoring, and debugging failures.
- 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.
- Experience with cloud infrastructure and infrastructure as code; comfortable working with containers, Kubernetes, CI/CD, access controls, and production observability.
- Track record of leading ambiguous infrastructure initiatives: setting technical direction, making pragmatic architecture tradeoffs, and driving adoption across teams.
- Clear communication and track record of partnering across teams while owning systems through production support.
DESIRABLE:
- GCP services such as Pub/Sub, Dataflow, Datastream, BigQuery, GKE, and Cloud Storage.
- Astronomer, Apache Beam, Terraform, Spacelift, Datadog, dbt, Spark or Dataproc.
- Supporting both batch and low-latency consumers, including product-facing data services or ML features.
- Experience supporting ML or AI workloads such as inference pipelines, reproducible evaluations, or governed data access.
