Staff Data Platform Engineer
$190,000–$240,000 year
Hybrid · New York City, New York, United States or San Francisco, California, United States
Job Summary
Staff Data Platform Engineer responsible for the reliability, stability, and operational health of Tatari's data platform across environments, administering, scaling, hardening, and evolving it. Enforce and improve environment promotion discipline (staging vs prod), define and uphold deployments SOPs, and instrument/monitor platform health with observability tooling. Participate in architecture and deployment discussions, collaborate with data scientists, engineers, and product managers as a partner, and identify remediation for reliability risks before incidents. This role focuses on infrastructure and systems reliability rather than data engineering, with a preference for candidates leaning SRE and with data platform experience. Qualifications emphasize cloud infrastructure/SRE experience (AWS preferred), high-availability architectures, distributed data processing, containerization/orchestration, data ingestion/ETL/streaming, IaC, databases, monitoring, and security; strong communication, ownership, and independent project delivery are valued. Benefits include compensation in the range of $190,000–$240,000, equity, health insurance, 401K, education benefits, PTO, wellness day, snacks, hybrid in-office schedule, and other perks.
Required Qualifications
- 3+ years in cloud infrastructure, SRE, or platform engineering (AWS preferred)
- Strong Linux fundamentals
- Containerization and orchestration (Kubernetes, Docker)
- Experience with workflow orchestration (Airflow)
- Data ingestion, ETL, or streaming systems (Kafka, Flink)
- Distributed data processing (Spark, PySpark)
- Infrastructure-as-code (Terraform, Helm)
- OLAP/OLTP databases (Postgres, Redshift, ClickHouse)
- Monitoring/observability tools (Datadog, Prometheus, Kibana)
- Databricks or similar managed data platforms (administering and scaling)
- Security and access management
- MLOps concepts or tooling is a plus
- Ability to collaborate across data scientists, engineers, and product managers
- Operational discipline and ownership
- Ability to scale and harden data platform infrastructure
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