Senior Data Engineer; Boston, MA

As a Senior Data Engineer, CASM Platform, you will:

• Data Integration, API Development:
  Integrate diverse cybersecurity data sources using a variety of API mechanisms and to standardize and streamline data across the data and user planes.
• Build and maintain data APIs for seamless access to data pipelines, enabling real‑time insights for applications, machine learning models, and analytical layers.
• Data Pipeline Engineering Optimization:
  Design, develop, and optimize large‑scale ETL/ELT pipelines on Databricks to efficiently process and transform cybersecurity data. Utilize Python, PySpark, and Databricks to automate and standardize data workflows across stages (raw, cleaned, curated), ensuring scalability and high performance.
• Data Quality & Governance:
  Implement automated data quality checks, leveraging Databricks DQM tools and CI/CD pipelines to uphold data integrity and governance standards. Ensure data lineage, metadata management, and compliance with cybersecurity and privacy regulations, applying rigorous quality standards across data ingestion and processing workflows.
• Data Analytics & Visualization:
  Design centralized data models and perform in-depth data analysis to support cybersecurity and risk management objectives. Develop visualizations and dashboards using tools like Databricks, encapsulate data to spin up to React.js application layer to provide stakeholders with actionable insights into threat landscapes, vulnerability trends, and performance metrics across the platform.
• Scalable & Secure Data Architecture:
  Architect and manage secure, high‑performance data environments on Databricks, utilizing AWS services such as S3, ELB, and Lambda. Ensure data availability, consistency, and security, aligning with AWS best practices and data encryption standards to safeguard sensitive cybersecurity data.
• Agile Product & Engineering Continuous Delivery:
  Collaborate with advanced Agile Product & Engineering cross‑functional teams to deliver data‑driven insights through analytics tools and custom visualizations that inform strategy and decision‑making. Empower stakeholders with timely, actionable intelligence from complex data analyses, enhancing their ability to respond to evolving cybersecurity risks.
• Data Science & ML Integration:
  Deploy machine learning models, including predictive analytics, anomaly detection, and risk scoring algorithms, into the CASM platform. Leverage Python and PySpark to enable real‑time and batch processing of model outputs, enhancing CASM Platform’s proactive threat detection and response capabilities.
• Mentorship & Best Practices Promotion:
  Mentor junior engineers, establishing best practices in data engineering, Dev Ops, data science, and analytics. Encourage high standards in model deployment, data security, performance optimization, and visualization practices, fostering a culture of innovation and excellence.

Minimum Qualifications

• Education:
  
  B.S., M.S., or Ph.D. in Computer Science, Data Science, Information Systems, or a related field, or equivalent professional experience.
• Technical Expertise: 8+ years in data engineering with strong skills in Python, PySpark, SQL, and extensive, hands‑on experience with Databricks and big data frameworks. Expertise in integrating data science workflows and deploying ML models for real‑time and batch processing within a cybersecurity context.
• Cloud Proficiency:
  Advanced proficiency in AWS, including EC2, S3, Lambda, ELB, and container orchestration (Docker, Kubernetes). Experience in managing large‑scale data environments on AWS, optimizing for performance, security, and compliance.
• Security Integration:
  Proven experience implementing SCAS, SAST, DAST/WAS, and secure Dev Ops practices within an SDLC framework to ensure data security and compliance in a high‑stakes cybersecurity environment.
• Data Architecture:
  Demonstrated ability to design and implement complex data architectures, including data lakes, data warehouses, and lake house solutions. Emphasis on secure, scalable, and highly available data structures that support ML‑driven insights and real‑time analytics.
• Data Quality & Governance:
  Hands‑on experience…