Senior Software Engineer – Data Engineering

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6 hours ago

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Abnormal Security

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Abnormal provides total protection against the widest range of attacks including phishing, malware, ransomware, social engineering, executive impersonation, supply chain compromise, internal account compromise, spam, and graymail.

501 - 1000 employees

📋 Description

• Own mission-critical pipeline reliability: Take end-to-end ownership of our production data pipelines processing billions of messages weekly, ensuring 99.9% uptime for revenue-critical pipelines that directly enable sales and customer-facing AI products • Build self-healing pipelines: Design and implement automated monitoring, testing, and recovery systems for data pipelines that eliminate manual intervention and reduce MTTR from hours to minutes • Accelerate development velocity: Deploy CI/CD pipelines and self-service platforms that reduce deployment time from 3-5 days to under 2 hours, enabling Data Scientists to safely deploy models without engineering bottlenecks • Architect for scale: Optimize data pipelines handling exponential annual growth, implementing cost-effective solutions that support regional expansion and compliance requirements (GDPR, FedRAMP, SOC2) • Bridge technical and business domains: Partner with Sales, Finance, and Product teams to ensure data infrastructure aligns with business needs, making critical trade-off decisions when pipelines impact revenue • Establish data engineering excellence: Define best practices for dbt, Airflow, Spark usage, PII anonymization, and cross-divisional data sharing while mentoring embedded Data Guild team members on these. • Enable AI and accessible data consumption: Design and maintain an accessible semantic layer that provides consistent, trustworthy definitions and abstractions, making it easy for stakeholders to consume data and incorporate AI-driven insights into their workflows.

🎯 Requirements

• 6+ years of software engineering experience in backend, distributed systems, or data-focused roles. • Proven experience designing and running large-scale, production-grade data pipelines. • Proficiency in our stack: Python, Spark/PySpark, Airflow, SQL, dbt, Databricks, Snowflake, AWS. • Proven track record of driving pipeline reliability to 99%+ uptime, including SLAs, observability tooling, and automated recovery patterns. • Strong systems-thinking skills with the ability to debug complex distributed systems, optimize for performance and cost, and make architectural decisions balancing short-term needs with long-term scalability. • Demonstrated ownership mindset and ability to drive projects from conception to production independently, including on-call responsibilities for critical systems. • Experience collaborating with Data Science, Analytics, Product, Finance, Marketing, and Sales, along with the ability to communicate technical decisions clearly to non-technical stakeholders and executives. • Bachelor’s degree in Computer Science, Applied Sciences, Information Systems or other related quantitative fields.

🏖️ Benefits

• Bonus • Restricted stock units (RSUs)