Data Platform Engineer

## Staff Data Platform Engineer Apply:
Portland, ME:
Bay Area, CA:
Seattle, WA:
San Francisco, CA:
Chicago, IL:
Full time:
Posted Today:
R16225

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations:
Portland, ME;
Boston, MA;
Chicago, IL;
Dallas, TX;
San Francisco Bay Area, CA; and Seattle/WA.
** About the Team/Role
** The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform.

We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and Dev Ops specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations.

**** How you’ll make an impact
**** Infrastructure, Orchestration & Dev Ops
* Airflow Infrastructure Ownership:
Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows.
* Infrastructure-as-Code & Git Ops:
Drive Dev Ops practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted Git Hub runners, and enforce Git Ops workflows.
* CI/CD & Automation:
Architect and manage robust CI/CD pipelines utilizing Git Hub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs.
* Container & Cluster Management:
Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS).
* Observability, Telemetry & Alerting:
Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability.

Central Data Platform, Tools & Governance
* Big Data Platform Architecture:
Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt.
* Data Lineage & Governance:
Deploy and maintain central data discovery and metadata tooling (e.g., Data Hub) to facilitate data governance, schema management, and cataloging.
* Cost Optimization & Fin Ops:
Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes).
* Developer Experience & Tooling:
Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists.

Technical Leadership & Ownership
* Architecture & End-to-End Ownership:
Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management.
* Technical Excellence & Best Practices:
Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management).
* Strategic

Roadmap:

Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap,…