Title : Sr Data Engineer (CASM Platform)
Location : hybrid in Boston MA
Duration : 612 months contract
Job Description : Who we are looking for :
- The CASM (Cyber AI App & Attack Surface Management) Platform Product & Engineering team is looking for a Sr. Data Engineer Cyber AI App & Attack Surface Management. CASM Platform team is focused on building enterpriselevel robust and scalable Cyber AI applications and Platform to manage vulnerability risk security configurations and attack surfaces oversight across the client. We are seeking an experienced handson Senior Data Engineer to join our CASM Platform team. Ideal candidates bring a deep understanding of data engineering within a cybersecurity context extensive experience with cloudnative tools (especially AWS) and a passion for automation security intelligent orchestration and resilience. Youll work in highpaced Agile Product & Engineering crossfunctional teams including Product AI application DevOps and Data Quality Management (DQM) to transform the CASM platform into a single pane of glass for secure and insightful network asset and risk visibility. We have multiple openings for this role and it is open to candidates with varying levels of experience.
Role Responsibilities : As a Senior Data Engineer CASM Platform you will :
Data Integration & API Development : Integrate diverse cybersecurity data sources using 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 realtime insights for applications machine learning models and analytical layers.Data Pipeline Engineering & Optimization : Design develop and optimize largescale 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 indepth 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 highperformance 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 crossfunctional teams to deliver datadriven insights through analytics tools and custom visualizations that inform strategy and decisionmaking. 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 realtime and batch processing of model outputs enhancing CASM Platforms proactive threat detection and response capabilities.Mentorship & Best Practices Promotion : Mentor junior engineers establishing best practices in data engineering DevOps data science and analytics. Encourage high standards in model deployment data security performance optimization and visualization practices fostering a culture of innovation and excellence.Education & Qualifications : 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 : 10 years in data engineering with strong skills in Python PySpark SQL and extensive handson experience with Databricks and big data frameworks. Expertise in integrating data science workflows and deploying ML models for realtime 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 largescale data environments on AWS optimizing for performance security and compliance.Security Integration : Proven experience implementing SCAS SAST DAST / WAS and secure DevOps practices within an SDLC framework to ensure data security and compliance in a highstakes 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 MLdriven insights and realtime analytics.Data Quality & Governance : Handson experience with automated data quality checks data lineage and governance standards. Proficiency in Databricks DQM or similar tools to enforce data integrity and compliance across pipelines.Data Analytics & Visualization : Proficiency with analytics and visualization tools such as Databricks Power BI and Tableau to generate actionable insights for cybersecurity risks threat patterns and vulnerability trends. Skilled in translating complex data into accessible visuals and reports for crossfunctional teams.CI / CD and Automation : Experience building CI / CD pipelines that automate testing security scans and deployment processes. Proficiency in deploying ML models and data processing workflows using CI / CD ensuring consistent quality and streamlined delivery.Agile Experience : Deep experience in Agile / Scrum environments with a thorough understanding of Agile core values and principles effectively delivering complex projects with agility and crossfunctional collaboration.Preferred Experience :
Advanced Data Modeling & Governance : Expertise in designing data models for cybersecurity data analytics emphasizing data lineage federation governance and compliance. Experience ensuring security and privacy within data architectures.Machine Learning & Predictive Analytics : Experience deploying ML algorithms predictive models and anomaly detection frameworks to bolster CASM platforms cybersecurity capabilities.HighPerformance Engineering Culture : Background in mentoring engineers in data engineering best practices promoting data science ML and analytics integration and fostering a culture of collaboration and continuous improvement.Key Skills
Apache Hive,S3,Hadoop,Redshift,Spark,AWS,Apache Pig,NoSQL,Big Data,Data Warehouse,Kafka,Scala
Employment Type : Full Time
Vacancy : 1
