Senior Azure Data Engineer – Cybersecurity Data Lakehouse & Data Pipelines

Be Part Of A High-Performing Team

Join the information security technology organization of a leading global financial institution committed to protecting sensitive information, strengthening cybersecurity capabilities, and maintaining a secure, compliant banking environment.

This opportunity supports a collaborative cybersecurity data engineering team focused on modernizing how security information is collected, integrated, and governed across the enterprise. The team is advancing a centralized cybersecurity data lakehouse initiative to improve visibility into sensitive data, strengthen information protection controls, and enable more effective security analytics.

The position works closely with cybersecurity engineering, information protection, and data operations stakeholders to deliver scalable cloud-based data solutions.

What's In Store For You

• Hybrid opportunity – Jersey City, NJ. Onsite frequency to be confirmed.
• Engagement: W2 only (no C2C/1099).
• Opportunity to contribute to a high-impact cybersecurity data modernization initiative within a global financial services environment.
• Work with Microsoft Azure data technologies while supporting enterprise security, compliance, and data governance objectives.
• Collaborate with experienced cybersecurity engineers, data owners, and information security professionals.
• Participate in an Agile delivery environment with established software development lifecycle processes.

How You Will Make An Impact

• Design, develop, and maintain Azure-based data ingestion pipelines supporting an enterprise cybersecurity data lakehouse.
• Integrate multiple cybersecurity data sources, particularly those supporting Data Security Posture Management (DSPM) and Data Loss Prevention (DLP).
• Develop scalable data transformation and processing workflows using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
• Support the centralization, standardization, and governance of cybersecurity datasets to improve data accessibility, reliability, and consistency.
• Collaborate with information security teams, data owners, and security engineers to translate technical and business requirements into actionable data engineering solutions.
• Troubleshoot ingestion failures, data quality issues, pipeline performance problems, and integration challenges.
• Implement appropriate data security, access controls, and compliance considerations throughout the data engineering lifecycle.
• Participate in Agile sprint planning, development activities, testing, documentation, and production delivery.
• Provide timely project updates, track development progress, and maintain alignment with established SDLC standards.

Requirements

Do You Bring Proven Success in Azure Data Engineering and Enterprise Data Integration?

• Senior-level data engineering background, with 10+ years of overall relevant experience aligned with the requisition's seniority designation.
• Strong hands-on experience designing, developing, and supporting data ingestion pipelines within Microsoft Azure environments.
• Practical expertise with Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
• Experience building or maintaining cloud-based data lakes, lakehouses, or enterprise data integration platforms.
• Strong understanding of ETL/ELT processing, data transformations, integration patterns, and data quality management.
• Knowledge of data security, governance, and compliance principles in enterprise environments.
• Ability to troubleshoot complex data pipelines and work across multiple source systems.
• Experience collaborating with technical and business stakeholders to gather requirements and coordinate delivery.
• Familiarity with Agile methodologies, sprint planning, and enterprise SDLC processes.
• Strong analytical, problem-solving, documentation, and communication skills.
• Relevant Microsoft Azure certifications are desirable; the requisition references certifications but does not specify a mandatory credential.
• Experience with cybersecurity data, DSPM, DLP, or regulated financial services environments is particularly valuable.