Senior Software Engineer (Data Engineer)

• Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
• Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
• Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
• Build a massive, fast-growing business with billions in revenue
• Handshake is hiring a Senior Data Platform Engineer to build and operate the infrastructure that moves data reliably across our career marketplace and AI products
• On the Data and ML Platform team, you will own the systems that orchestrate batch workloads and deliver timely, trustworthy data to engineers, analysts, and product teams
• This is a hands-on technical leadership role with the opportunity to shape Handshake’s data infrastructure strategy. You will set the technical direction for our workflow orchestration platform (Airflow), data ingestion, data pipelines, our data warehouse (BigQuery) and streaming data infrastructure
• You’ll collaborate closely with ML engineers, data scientists, and other engineers to maximize velocity on our data platform. This infrastructure will also support Handshake’s growing AI development, from model and agent workflows to evaluation and production data access
• Lead the technical direction and roadmap for our Airflow and Astronomer platform while owning its 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 clear runbooks
• Design and operate streaming and change data capture pipelines using tools such as Pub/Sub, Dataflow or 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 useful latency, freshness, and reliability targets
• Improve the 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 platform approaches
• Participate in on-call, troubleshoot production failures across systems, and turn incidents into durable improvements
• Build dependable data and orchestration foundations for AI workloads, including batch inference, evaluation datasets, and agent-facing data

Benefits

• Health Insurance: Comprehensive medical , dental, and vision coverage
• Fertility and family forming: Through a partnership, Handshake offers comprehensive family benefits, including infertility treatments and a $15K stipend, to its employees.
• LGTBQ+ coverage: All medical plans cover transgender services.
• Mental health: Discounts on a variety of wellness apps and an Employee Assistance Program with access to five free counseling sessions.
• Tax savings: Tax-advantaged benefits to save money on healthcare, dependent care, and other expenses.
• Life & disability insurance: Essential benefits and automatic coverage with basic life insurance, plus short-term and long-term disability coverage.
• 401k match: Dollar-for-dollar match up to 1% of pay, with a max of $1,200 per year.
• Equity: Our equity program includes grants at hire, refresher grants after two years of tenure, and grants alongside promotions.
• Financial management: Handshake partners to provide free professional financial planning services.
• Learning & development: Employees are provided with an annual stipend to use towards professional development, career development workshops, manager trainings, and 1-on-1 coaching through external partnerships
• Community leader support: Employee Resource Group leaders are compensated with a quarterly bonus for the high-impact work the role requires
• Parental leave: Leaves of 16 weeks for birth-giving parents and 10 weeks for non-birth-giving parents; the policy applies to adoptions as well. Handshake also partners to provide one-on-one coaching on preparing for leave and coming back from leave
• Flexible time off: No accrued time off or waiting period to take vacation. Two paid flexible holiday days off to observe holidays that closely align with religious, cultural, and personal needs
• Sabbatical: Paid six-week sabbatical to recharge and reset beginning at six years of continuous, full-time employment, and every four years thereafter
• Volunteer time off: Two days off for social and civil activism, volunteer work, and/or any related activities, including attending and participating in protests

• Experience with cloud infrastructure and infrastructure as code; comfortable working with containers, Kubernetes, CI/CD, access controls, and production observability
• Clear communication and a track record of partnering across teams while owning systems through production support
• 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
• 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