Job Description

At

SAFE Security

, our vision is to be the

Champions of a Safer Digital Future and the Catalysts of Change

. We believe in empowering individuals and teams with the freedom and responsibility to align their goals, ensuring we all move forward together.

We operate with

radical transparency, autonomy, and accountability

--there's no room for brilliant jerks. We embrace a

culture-first approach

, offering an

unlimited vacation policy

, a high-trust work environment, and a commitment to continuous learning. For us,

Culture is Our Strategy

--check out our

Culture Memo

to dive deeper into what makes SAFE unique.

We're looking for a seasoned Senior Software Development Engineer (SDE III) - Data Engineering with deep expertise in building large-scale data ingestion, processing, and analytics platforms. In this role, you'll collaborate closely with Product, Design, and cross-functional stakeholders to design and implement high-throughput data pipelines and lakehouse solutions that power analytics, AI, and real-time decision-making for predicting and preventing cyber breaches.

What You'll Do:

+ Technical Leadership: Lead and mentor developers, fostering a culture of innovation, quality, and continuous improvement + Design and Develop: Architect and implement high-scale data pipelines leveraging Apache Spark, Flink, and Airflow to process streaming and batch data efficiently.
+ Data Lakehouse and Storage Optimization: Build and maintain data lakes and ingestion frameworks using Snowflake, Apache Iceberg, and Parquet, ensuring scalability, cost efficiency, and optimal query performance.
+ Data Modeling and System Design: Design robust, maintainable data models to handle structured and semi-structured datasets for analytical and operational use cases.
+ Real-time and Batch Processing: Develop low-latency pipelines using Kafka and Spark Structured Streaming, supporting billions of events per day.
+ Workflow Orchestration: Automate and orchestrate end-to-end ELT processes with Airflow, ensuring reliability, observability, and recovery from failures.
+ Cloud Infrastructure: Build scalable, secure, and cost-effective data solutions leveraging AWS native services (S3, Lambda, ECS, etc.).
+ Mentorship: Lead by example, guide junior engineers, conduct reviews, and drive adoption of best practices for data engineering excellence.
+ Monitoring and Optimization: Implement strong observability, data quality checks, and performance tuning to maintain high data reliability and pipeline efficiency.

What We're Looking For:

+ Bachelor's or Master's degree in Computer Science, Engineering, or a related field + 6+ years of experience in data engineering with a proven track record of designing large-scale, distributed data systems.
+ Strong expertise in Snowflake and other distributed analytical data stores.
+ Hands-on experience with Apache Spark, Flink, Airflow, and modern data lakehouse formats (Iceberg, Parquet).
+ Deep understanding of data modeling, schema design, query optimization, and partitioning strategies at scale.
+ Proficiency in Python, SQL, Scala, Go/Nodejs with strong debugging and performance-tuning skills.
+ Experience in streaming architectures, CDC pipelines, and data observability frameworks.
+ Ability to mentor engineers, review designs, and lead technical discussions.
+ Familiarity with using AI Coding assistants like Cursor, Claude Code, or GitHub Copilot.

Preferred Qualifications:

+ Exposure to CI/CD pipelines, automated testing, and infrastructure-as-code for data workflows. + Familiarity with streaming platforms (Kafka, Kinesis, Pulsar) and real-time analytics engines (Druid, Pinot, Rockset).
+ Understanding of data governance, lineage tracking, and compliance requirements in a multi-tenant SaaS platform.

If you're passionate about cyber risk, thrive in a fast-paced environment, and want to be part of a team that's redefining security--

we want to hear from you!