Security Data Engineering

Security Data Engineering Jobs

2 jobs found

1d ago

Security Data Engineer

Deloitte Colorado Springs, CO

Colorado Springs, CO

1d ago

$96k - $159k/yr Full time Cybersecurity Operations Data Data Analysis

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Job Description

Join Deloitte’s Enterprise Security team to support clients with designing, implementing, and improving enterprise security solutions.

Responsibilities

Design, write, and deploy high-fidelity detection rules using SQL, Sigma, YARA-L, or Python targeting network-based attack techniques such as C2 beaconing, data exfiltration, and lateral movement.
Continuously tune network detections to reduce false positives while maintaining a high signal-to-noise ratio.
Determine the telemetry needs for network monitoring, threat hunting, incident response, and custom detection engineering.
Map detection requirements to underlying data sources and identify visibility gaps across hybrid cloud and on-premises environments.
Design and maintain telemetry ingestion pipelines for security telemetry from network, endpoint, identity, cloud, application, OT, and security infrastructure.
Ensure telemetry is delivered reliably to SIEM, data lake, analytics, and detection platforms.
Troubleshoot ingestion and processing issues including ingestion failures, parsing, latency, and data-quality problems.
Evaluate whether packet, flow, session, DNS, proxy, authentication, endpoint, and application telemetry is sufficient for specific detection requirements.
Support custom detection development with data discovery, enrichment, normalization, and validation.
Identify opportunities to move detections from lower-level indicators toward behavioral and tradecraft-based detection using the Detection Stack.
Collaborate with network engineering to evaluate network sensor and telemetry technologies, including NetFlow/IPFIX, DNS telemetry, proxy telemetry, firewall logs, IDS/IPS, packet capture, Zeek/network metadata, and NDR platforms.
Establish telemetry health metrics, dashboards, and automated checks for missing, delayed, or malformed data.
Assess network visibility across data centers, cloud environments, remote networks, and segmented environments.
Optimize telemetry architectures and ingestion pipelines for performance, scalability, reliability, and cost.

Requirements

Bachelor’s degree in Cybersecurity or Information Technology.
Active TS/SCI or SCI eligibility.
4+ years of experience in cybersecurity, enterprise security, or information security.
3+ years supporting implementation or administration of security technologies across enterprise environments.
3+ years producing technical documentation, status reporting, or client deliverables for security engagements.

Technologies

SQL
Sigma
YARA-L
Python
SIEM
Detection Stack
NetFlow/IPFIX
IDS/IPS
Zeek
NDR
Packet capture

Location

Colorado Springs, CO (onsite)

Salary

USD 95,600 - 159,300 per year

Benefits

Eligible for a benefits package competitive for project delivery-focused professionals.
May be eligible to participate in a discretionary annual incentive program, subject to program rules.

Preferred

Master’s degree in Cybersecurity, Information Technology, Information Systems, Engineering or related field with 10+ years of related experience.
Experience supporting government or public sector clients.
Experience with cloud security, data security, and network security.

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9d ago

Data Engineer III - Python, Databricks

JPMorganChase Houston, TX

Houston, TX

9d ago

Full time Python Amazon Web Services AWS

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Job Description

Build secure, scalable data pipelines and analytics foundations using Python and Databricks in an onsite Houston environment.

Responsibilities

Develop workflows and ELT pipelines using Python and Databricks.
Support review of controls to ensure sufficient protection of enterprise data.
Implement data security using entitlements frameworks.
Update logical or physical data models as new use cases emerge.
Use SQL frequently and apply working knowledge of NoSQL databases.
Apply enterprise-authorized AI capabilities within the work environment to accelerate data pipeline and design analysis/documentation.
Validate AI-assisted outputs and handle data according to sensitivity and security requirements.
Use reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (including test generation and control validation).
Ensure traceability/auditability and alignment to resiliency and security expectations.

Requirements

Formal training or certification on software engineering concepts and 3 years of applied experience.
Good working knowledge of AWS, Databricks, and Python, with experience across the data lifecycle.
Advanced SQL skills, including joins and aggregations; working understanding of NoSQL databases.
Significant experience with statistical data analysis and the ability to select appropriate tools and data patterns.
Ability to utilize AWS Cloud Services to develop, deploy, and manage applications at scale.
Proficiency with AI coding assistants, using tools daily such as Cursor, GitHub Copilot, and Claude for code generation, documentation, and refactoring.
Prompt engineering skills: provide context, clear goals, relevant source material, and defined output expectations to produce accurate, usable code.
Critical evaluation and validation to identify hallucination patterns, security vulnerabilities, and logic errors in AI-generated code before production deployment.
Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted outputs (query suggestions, test ideas, model change summaries) before use; escalate when uncertain and follow data handling requirements.

Preferred Qualifications, Capabilities, and Skills

Familiarity with Standardized data layer practices, including Medallion architecture.
Exposure to Aurora Postgres and MongoDB.
Experience developing and supporting AWS GLUE Jobs and Federated Data Lake.
Skills in designing efficient data models, including normalization, denormalization, and schema design, with understanding of relational and star schemas.
Augmented development workflow: integrating tools into CI/CD pipelines, using containerization (for example, Docker), and leveraging AI to bridge language gaps (for example, transitioning between Python, JavaScript, or Java).

Technologies

Python, Databricks, ELT, SQL, NoSQL
AWS, AWS GLUE Jobs, Federated Data Lake, Aurora Postgres
Medallion architecture
Cursor, GitHub Copilot, Claude
Docker, CI/CD
MongoDB, Federated Data Lake
JavaScript, Java

Benefits

Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

Location: Houston, TX (onsite)

Minimum Experience: 3 years

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Security Data Engineering Jobs

Security Data Engineer

Data Engineer III - Python, Databricks

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