Staff Data Infrastructure Engineer
Staff-level Data Infrastructure Engineer to architect and evolve the data platform (Snowflake, ingestion, orchestration, CI/CD, AWS infra) serving analytics, product, and ML teams. Requires 10+ years building scalable data platforms and proven technical leadership.
About the job
Experience we're seeking
- 10+ years as a Data Platform Engineer, Software/Infrastructure Engineer specializing in data, or Data Engineer in a high-code, high-scale environment
- Track record of driving technical strategy and cross-functional alignment, including defining roadmaps for a data platform or infrastructure domain
- Deep expertise building full-stack data platforms: data warehousing, ingestion pipelines, orchestration, monitoring and alerting, CI/CD, developer tooling, cloud infrastructure, and third-party integrations
- Architectural fluency in warehouse design patterns, performance tuning, cost management, and permissions strategies on MPP analytics databases (Snowflake strongly preferred; Databricks, BigQuery, or Redshift also relevant)
- Experience leading technical initiatives end-to-end across multiple teams and codifying engineering standards
- Proficiency designing and operating cloud infrastructure at scale (AWS preferred) using infrastructure-as-code (Terraform, Pulumi, AWS CDK)
- Strong Python engineering skills; solid SQL foundations; comfort with distributed systems
- Experience maintaining and scaling pipeline orchestration infrastructure (Airflow/Astronomer preferred)
- Mentorship track record growing junior and mid-level engineers
Bonus points for
- Agentic Data Engineering (automating data infrastructure tasks, auditing permissions, optimized CI)
- APM and observability tooling (DataDog, New Relic) and data quality/observability frameworks
- ETL/ELT best practices at scale
- Data security and compliance in regulated environments, especially PHI
- Greenfield platform development in a high-growth startup
- Docker, GitHub Actions, dbt, Spark
- Build vs. buy decision-making and vendor evaluation
Compensation and Benefits
The expected base pay range for this position is $212,000 - $265,000. In addition to base salary, this role may be eligible for an equity grant.
Benefits offered include:
- Equity compensation
- Medical, Dental, and Vision coverage
- HSA / FSA
- 401K
- Work-from-Home Stipend
- Therapy Reimbursement
- 16-week parental leave for eligible employees
- Carrot Fertility annual reimbursement and membership
- 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st
- Flexible PTO
- Employee Assistance Program (EAP)
- Training and professional development
Skills
Snowflake, AWS, Terraform, Python, SQL, Airflow, Docker, GitHub Actions, dbt, Spark
Similar jobs
Data Engineering jobsStaff Software Engineer leading development of data catalog and metadata infrastructure for discovery, governance, lineage, and quality across Airbnb’s data ecosystem. Requires 9+ years of software engineering experience focused on data infrastructure and strong programming and distributed data technology skills.
Staff Software Engineer responsible for architecting, building, and operating Commure’s data warehouse platform, including CDC, lakehouse, query, transformation, and analytics layers. Requires 6+ years of software engineering experience and broad expertise across modern production data infrastructure.
Senior individual contributor responsible for architecting and scaling production data ingestion systems that integrate complex enterprise sources into reliable datasets. Requires 5+ years of backend engineering experience, strong Python, cloud, Kubernetes, Postgres, and data integration expertise.
This staff-level data engineer will architect and operate low-latency market data infrastructure, including feed handling, normalization, distribution, and exchange connectivity. The role requires at least five years of backend engineering experience and strong Java or C++ expertise with high-throughput messaging and market data protocols.
Analytics Engineer supporting Go-to-Market teams by building scalable data models, metrics, pipelines, visualizations, and self-service products. The role requires 10+ years of data experience, deep SQL expertise, Python proficiency, and strong business judgment.