Senior Data Engineer - GCP

Responsibilities

Design and implement robust, scalable backend services in Node.js, Python, and other technologies to process and deliver real-time and batch data for analytics, personalization, and search. Integrate new data sources and improve existing ones using many different methods

Architect and manage cloud-native data infrastructure on GCP (e.g., BigQuery, Dataflow, Pub/Sub, Cloud Storage). Work primarily in Node JS for data extraction and transformation

Build and optimize data orchestration and deployment pipelines using Kubernetes and modern CI/CD tooling

Partner with frontend teams to expose data via internal dashboards, admin tools, and customer-facing components

Ensure data reliability, availability, and security across all services and systems

Collaborate with data scientists, analysts, and other engineers to build tools that unlock business insights from large-scale data

Help define data governance, quality, and observability standards

FinOps exposure/execution - you will have a lead role on a small team in cost auditing existing cloud infrastructure in GCP and proposing and collaborating on engineering changes needed to optimize cloud spends

Mentor other engineers and contribute to a culture of technical excellence and continuous learning

Requirements

8+ years of experience in backend or platform engineering, with a focus on data-intensive systems

Deep hands-on experience with Google Cloud Platform, including BigQuery, Pub/Sub, Cloud Functions, and GKE

Proficient in Kubernetes for deploying and scaling data services

Working knowledge of React for integrating backend systems with internal tools or dashboards

Solid understanding of data modeling, pipelines, and streaming architectures

Experience building and maintaining CI/CD pipelines for data applications

Strong experience working with Google Cloud Platform (GCP) – BigQuery, Dataflow, Pub/Sub, Cloud Storage, Kubernetes

Experience with FinOps best practices and auditing procedures

Strong understanding of deduplication to optimize data storage and reduce cloud costs

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