Senior FDE Data Engineer
New
Based in United StatesFull-TimeSenior
Salary$148,750 – $201,250 USD
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Job Details
- Required Skills
- KubernetesAirflowApache KafkaData engineeringPostgresLinuxTerraformDistributed Systems
Requirements
- Strong background in data engineering, distributed systems, or platform engineering across the full data stack.
- Hands-on experience with Kubernetes in production environments, including debugging, networking, and storage.
- Experience with data technologies such as Apache Iceberg, Postgres, S3-compatible object storage, and query engines like Trino, Spark, or ClickHouse.
- Knowledge of streaming and integration systems such as Kafka and CDC pipelines.
- Proficiency with data pipelines and orchestration tools such as Airflow, Dagster, or Argo Workflows.
- Familiarity with infrastructure-as-code and GitOps practices (Terraform, Pulumi, ArgoCD, or Flux).
- Strong Linux, networking, and container fundamentals with ability to debug system-level issues.
- Ability to operate autonomously in high-stakes environments and communicate with diverse stakeholders.
- Active U.S. government security clearance (TS/SCI preferred or ability to obtain).
- U.S. citizenship required.
Responsibilities
- Deploy and operationalize a full-stack data platform in mission-critical environments, including storage, streaming, governance, and Kubernetes-based infrastructure.
- Build and maintain end-to-end data pipelines that support ingestion, transformation, cross-domain movement, and classification boundary handling.
- Integrate the platform with existing systems including legacy databases, identity providers, object stores, and enterprise tooling.
- Own day-2 operations including observability, incident response, performance tuning, backups, upgrades, and system reliability.
- Produce accreditation and compliance artifacts such as security documentation, policy mappings, and operational evidence.
- Serve as a technical bridge between field users and internal engineering teams to capture feedback and drive platform improvements.
- Train users and internal stakeholders through documentation and knowledge transfer sessions.
- Mentor junior forward-deployed engineers by reviewing designs and pairing on complex problems.
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