Data Engineer

1 week ago

Quincy, United States LanceSoft Full time

Pay: $80-90/hr

As a Senior Data Engineer,

Education & 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 DevOps 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 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 cross-functional 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 cross-functional 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.

High-Performance 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.

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