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Sobre este puesto de Data Platform Engineer en Rain

Rain · Presencial · San Juan, Puerto Rico

About the Company

Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world.

You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk.

Our Ethos

We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company.

About the role

Rain is building payments and stablecoin infrastructure, and our data platform holds some of the most sensitive data a company can have: cardholder, ledger, and partner data across many countries.

We’re looking for a Data Platform Engineer who has built and run data platforms for both batch and streaming to own the platform our data team and engineering pods depend on: the warehouse, streaming infrastructure, orchestration, BI, ML platform, access controls, and the tooling that makes all of it safe, reliable, and cost-efficient. Your product is the platform, and your customers are the engineers, analysts, and scientists who build on it.

You’ll own the platform layer: the data and ML platform, the infrastructure for ingestion and processing in batch and streaming, data governance and security compliance, the warehouse, and the analytics and BI tooling. Data Engineers, Analytics Engineers, Data Scientists, and engineering pods build on it to run experiments, operate reliably, and turn data into decisions.

At Rain, we’re builders who use AI to automate repetitive work. That changes what data roles look like: where a data scientist used to only analyze and an analyst used to only build dashboards, here everyone models data, writes production-quality code, and automates their own workflows. You own the result, including checking what the AI produces. For this role, that means automating access, deploys, and governance so the platform runs itself and stays compliant.

What you’ll do

  • Design and build data platforms at scale for both batch and streaming, choosing storage, compute, and processing based on latency, cost, and reliability needs.

  • Own the infrastructure for BigQuery, streaming (such as Pub/Sub or Kafka, and Dataflow or Flink), Dagster+, and Lightdash as code, including environments, CI/CD, and deploys.

  • Own access and governance: IAM, policy tags, PII contracts, masked and no-PII access paths, and audit logs, across tables and streams.

  • Provide ML platform capabilities: feature pipelines, training data, and serving real-time features to fraud and risk models.

  • Build platform tooling: templates, CI checks, schema registry and data contracts, catalog, and lineage.

  • Monitor platform reliability, latency, and cost, and fix what is slow or expensive.

  • Design how backend events and CDC land in the warehouse, and advise backend pods on event design.

  • Respond to platform incidents and access requests, and automate the repetitive ones away.

What you’ll need

  • At least 4 years building and running data platforms in production on a cloud provider such as GCP, AWS, or Azure, in both batch and streaming: you have operated infrastructure for each, not only one.

  • Experience designing data platforms at scale: storage and compute choices, multi-team access, reliability, and cost.

  • Experience operating cloud data warehouses and real-time stores such as BigQuery and ClickHouse.

  • Experience operating streaming infrastructure such as Pub/Sub, Kafka, Dataflow, or Flink, including retention, schema evolution, replay, and lag monitoring.

  • Experience operating batch infrastructure: orchestration (Dagster or Airflow), CI/CD, and environments.

  • Infrastructure as code with Terraform.

  • Experience with access control and data governance, such as IAM, column- or row-level security, and PII handling.

  • Strong Python and SQL.

  • Proficiency using AI tools to learn new skills and accelerate your work, while taking responsibility for checking the output.

Nice to have

  • ML infrastructure experience, such as feature stores, Vertex AI, or model serving.

  • Experience in regulated environments such as payments, banking, PCI, or SOC 2.

  • Experience with data catalogs and lineage tools.

  • Experience with cost optimization in BigQuery, ClickHouse, or Snowflake.

  • Experience with CDC tools such as Datastream or Debezium.

Things that enable a fulfilling, healthy and happy experience at Rain:

Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves.

Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace.

Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan.

Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match.

Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success.

Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you!

In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit.

Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.


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Cómo se compara este salario de Data Engineer

Este puesto paga $153,061/yr — en línea con el rango típico para los puestos de Data Engineer.

$101,542 la mediana de $163,750 $240,000

Rango típico $129,463–$193,984/yr, a partir de 1,800 ofertas comparables de Data Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de Data Engineer →

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