Senior Software Engineer
Abnormal Security
Job highlights
Summary
Join Abnormal Security's Detection Team as a Senior Software Engineer! You'll build and deploy backend ETL jobs and infrastructure for a world-class detection engine, focusing on scalability and customer-centric solutions. Responsibilities include owning real-time data pipelines, collaborating with ML and Data Science teams, and mentoring junior engineers. The ideal candidate possesses extensive data engineering experience, expertise in ETL and data pipeline design, and a proven ability to collaborate effectively in a fast-paced environment. This role requires a strong background in building large-scale distributed systems on cloud platforms. You will play a key role in making Abnormal's feature development fast, responsive, stable, and confident for our ML and Data Science team.
Requirements
- 5+ years of experience as a data engineer or in a similar role, with hands-on experience in building data-focused solutions
- Expertise in ETL, data pipeline design, and data engineering tools and technologies (e.g., Apache Spark, Hadoop, Airflow, Kafka)
- Experience with maintaining real-time and near real-time data pipelines or streaming services at high scale
- Experience with maintaining large scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of best practices in cloud-based data engineering
- A background in implementing data quality frameworks including validation, monitoring, and anomaly detection to ensure data accuracy, consistency, and reliability. You know how to design checks and alerts to maintain data integrity and quickly respond to potential issues
- Proven ability to collaborate effectively with cross-functional teams, including data scientists, machine learning engineers, product managers, and other stakeholders. Youโre able to translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback
- Excellent problem-solving skills and the ability to work independently in a fast-paced environment. Youโre capable of breaking down complex challenges into manageable steps and iterating on solutions, balancing immediate needs with long-term scalability
Responsibilities
- Architect, design, build, and deploy backend ETL jobs and infrastructure that support a world-class Detection Engine
- Ownership projects that enable us to meet ambitious goals for, such as building the plan to scale components of Detectionโs Data Pipeline by 10x
- Own real-time, near real-time streaming pipelines and online feature serving services
- Collaborate closely with MLE and Data Science teams, by distilling feedback, correlating it to our strategy, and executing
- Coach and mentor junior engineers via 1on1s, pair programming, high quality code reviews and design reviews
Preferred Qualifications
- Familiarity with machine learning workflows and requirements to support data science teams effectively
- Experience with streaming data architectures and real-time processing
- Knowledge of security and compliance frameworks as they relate to data engineering and data privacy
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