Senior Data Platform Engineer

United StatesRemoteFull-timesenior

Data EngineerData

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Platform Engineer based in United States.

Technical Tools

Data EngineerData

This is a senior engineering role with end-to-end ownership of a production data platform running on Google Cloud.
You will build and operate the infrastructure that enables teams to use critical data safely, reliably, and efficiently.
The role combines infrastructure as code, CI/CD, data engineering, security, and platform reliability.
You will work closely with data scientists, analysts, infrastructure engineers, clinical integration specialists, and compliance partners.
A major focus will be protecting sensitive patient information through secure-by-default architecture and automated controls.
You will also remove infrastructure bottlenecks and help turn analytical work into dependable, production-ready data products.
This is an opportunity to shape a foundational platform while contributing to technology with a clear social and healthcare impact.

Own the Google Cloud data platform, including BigQuery, Datastream, Cloud Run functions and jobs, service accounts, IAM, and related infrastructure.
Manage data infrastructure through Terraform, using established modules and standards while ensuring production changes are delivered through code review and CI/CD rather than manual console changes.
Build and maintain CI/CD pipelines for datasets, data pipelines, and serverless workloads, keeping staging and production environments consistent and reproducible.
Establish monitoring, logging, alerting, and automated drift detection for data freshness, infrastructure failures, PHI controls, IAM permissions, and service exposure.
Implement secure-by-default practices for sensitive patient information, including PHI classification, column-level policy tags, masked views, least-privilege access, and internal-only service ingress.
Partner with infrastructure and compliance teams on access reviews, audits, security controls, migration planning, and operational runbooks.
Enable data scientists and analysts to work efficiently by providing safe self-service environments and clear paths from exploratory analysis to scheduled production workloads.
Help move analytical initiatives into production, including outcomes reporting and other data workloads tied to organizational objectives.
Own the data team's infrastructure backlog, identify and remove platform bottlenecks, and provide technical guidance that allows teams to focus on analysis rather than infrastructure maintenance.
Maintain clear documentation covering platform architecture, runbooks, data definitions, lineage, and operational procedures.
Establish measurable standards for platform reliability, security, deployment practices, and internal request turnaround, using defined KPIs to continuously improve the platform.

Requirements

~2 min read

Deep, hands-on experience with Google Cloud data infrastructure, including BigQuery, IAM, service accounts, and serverless technologies such as Cloud Run in production environments.
Proven experience managing infrastructure as code using Terraform or an equivalent technology, along with CI/CD platforms such as GitHub Actions.
Experience owning or operating a production data platform end to end, including data ingestion, change data capture, layered data warehouses, monitoring, and operational reliability.
Strong production-level SQL and Python skills, with the ability to build and maintain reliable data workloads.
Demonstrated experience securing sensitive or regulated data through controls such as least-privilege IAM, column-level security, policy tags, masked views, and automated security checks.
Experience working closely with data scientists, analysts, or other data-focused teams to remove infrastructure constraints and accelerate delivery.
Strong understanding of how cloud infrastructure and data services behave in production, including troubleshooting failures and addressing root causes.
Ability to establish reliable engineering practices around deployment, monitoring, documentation, and operational ownership.
Strong communication and collaboration skills, with the ability to work effectively across engineering, data, infrastructure, security, compliance, and other organizational teams.
A proactive, ownership-oriented approach, with the ability to operate independently, prioritize competing needs, and make thoughtful technical decisions.
Genuine interest in applying technology and reliable data infrastructure to healthcare access and health equity.