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About the Role
We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join our Data Platform Engineering Team. This role involves taking 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.
Responsibilities
- Design, deploy, scale, and maintain highly available Apache Airflow clusters.
- Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments.
- Manage self-hosted GitHub runners and enforce GitOps workflows.
- Architect and manage robust CI/CD pipelines utilizing GitHub Actions.
- Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS and Azure.
- Build and maintain end-to-end monitoring, logging, and alerting systems.
- Build scalable data infrastructure supporting big data processing engines and data warehouses.
- Deploy and maintain central data discovery and metadata tooling.
- Actively monitor, audit, and optimize data infrastructure compute and storage costs.
- Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity.
- Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management.
- Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security.
- Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps and define a data platform roadmap.
- Serve as a subject matter expert on data infrastructure, guiding and mentoring junior and mid-level data platform engineers.
Requirements
- 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments.
- Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure.
- Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions.
- Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki.
- Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka.
- Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure.
- Demonstrated history of driving cloud cost optimization.
- Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms.
- Strong programming skills in Python, Bash, Go, or SQL.
- Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment.
- Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure.
Skills
- Apache Airflow
- Kubernetes
- Helm
- Terraform
- Docker
- ArgoCD
- GitHub Actions
- Grafana
- Prometheus
- Loki
- Apache Spark
- AWS EMR
- Snowflake
- Azure Synapse
- dbt
- Apache Kafka
- AWS
- Azure
- DataHub
- Amundsen
- Python
- Bash
- Go
- SQL
- CI/CD
- DevOps
- SRE
- GitOps
- Observability
- Data Governance
- Cloud Cost Optimization
- FinOps
- ETL/ELT
- Containerization
- Infrastructure-as-Code
Location
- Remote
- Portland, ME
- Boston, MA
- Chicago, IL
- Dallas, TX
- San Francisco Bay Area, CA
- Seattle, WA
Work Type
- Remote
Experience Level
- Staff
- 6+ years
Salary/Compensations
- $140,600.00 - $173,100.00
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Retirement savings plan
- Paid time off
- Health savings account
- Flexible spending accounts
- Life insurance
- Disability insurance
- Tuition reimbursement
About the Company
- 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.