# Software Engineer - Data Infrastructure

**Company:** [Fable Security](https://hotfix.jobs/companies/fable-security)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $160k – $225k/yr
**Experience:** 3+ years
**Skills:** Spark, Kafka, dbt, Airflow, AWS, GCP, ETL, ELT, Data Warehousing, Data Lakes, Orchestration, Stream Processing, Data Modeling, Observability, ML Infrastructure
**Posted:** 2026-04-06

> Builds and maintains scalable data pipelines, infrastructure, and tooling for batch/streaming processing, ML workflows, and analytics. Requires 3-7+ years in data infrastructure with expertise in Spark, Kafka, dbt, Airflow, and cloud platforms.

## Job Description

## Responsibilities
- Design, build, and maintain scalable data pipelines and infrastructure
- Develop batch and streaming systems for ingesting and processing large-scale data
- Own core components of the data platform (warehouse, lake, orchestration, tooling)
- Implement data modeling, transformation, and versioning frameworks
- Ensure data quality, observability, and reliability across pipelines
- Optimize systems for performance, cost, and scalability
- Build tooling to support reproducible datasets and experimentation
- Partner with data scientists and engineers to productionize ML and analytics workflows
- Contribute to secure and compliant data infrastructure in cloud environments

## Requirements
**Must-Have:**
- 3–7+ years of experience in data infrastructure, infrastructure, or platform engineering
- Strong understanding of real-time and batch data processing systems, including stream processing, messaging architectures, and large-scale data workflows (Spark, Kafka, etc.)
- Experience with modern data tooling (dbt, Airflow, etc.)
- Strong understanding of data modeling, ETL/ELT, reverse ETL, and orchestration
- Experience designing for scalability, reliability, and observability
- Hands-on experience with cloud platforms (AWS/GCP) and storage systems
- Ability to operate in a fast-moving startup environment with high ownership

**Nice-to-Have:**
- Familiarity with ML infrastructure or feature stores
- Experience with data versioning, lineage, or reproducibility systems
- Background in security, compliance, or high-sensitivity data domains
- Previous experience at an early-stage startup

## Compensation
- Estimated salary range: $160K - $225K / year
- Total compensation may include Restricted Stock units, sign-on bonus and other potential future incentives

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