Software Development Engineer II
8 hours ago
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 Software Development Engineer (SDE II) – 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:
- 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.).
- Monitoring and Optimization: Implement strong observability, data quality checks, and performance tuning to maintain high data reliability and pipeline efficiency.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 3+ 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.
- Proficient in deploying containerized applications (Docker, Kubernetes, ECS).
- Familiarity with using AI Coding assistants like Cursor, Claude Code, or GitHub Copilot
- 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.
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