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Key Responsibilities and Required Skills for Data Security Engineer

💰 $110,000 - $170,000

SecurityData EngineeringCloudCompliance

🎯 Role Definition

As a Data Security Engineer you will design, implement, and maintain technical controls that protect sensitive data across cloud and on-prem systems. You will work cross-functionally with engineering, product, privacy, and compliance teams to embed security and privacy into data platforms, ETL pipelines, data warehouses (Snowflake, BigQuery, Redshift), streaming systems (Kafka), and analytics tools. This role combines applied cryptography, identity and access management, data loss prevention, threat modeling and operational incident response to ensure data confidentiality, integrity, availability, and regulatory compliance (GDPR, HIPAA, SOC 2, ISO 27001).

📈 Career Progression

Typical Career Path

Entry Point From:

  • Security Engineer (Application/Cloud)
  • Data Engineer with security focus
  • Cloud Infrastructure Engineer or DevOps Engineer

Advancement To:

  • Senior Data Security Engineer
  • Lead/Principal Data Security Engineer
  • Manager/Director of Security or Data Protection
  • Head of Data Security or Chief Information Security Officer (CISO)

Lateral Moves:

  • Data Privacy / Privacy Engineer
  • Data Governance or Data Architect
  • Compliance / Risk Manager

Core Responsibilities

Primary Functions

  • Design and implement robust encryption strategies for data at rest and in transit, including selecting algorithms, managing key lifecycles, integrating with cloud KMS (AWS KMS, GCP KMS, Azure Key Vault) and HSMs, and documenting cryptographic decisions and tradeoffs.
  • Build and maintain data loss prevention (DLP) controls across cloud storage, data warehouses, messaging systems, and endpoints; author DLP rules, tune detection to reduce false positives, and automate remediation workflows.
  • Define and enforce fine-grained access controls for data platforms (RBAC, ABAC), implement least-privilege patterns, manage service accounts and IAM roles, and automate access provisioning and periodic access reviews.
  • Integrate security and privacy controls into CI/CD pipelines: scan data transformations, ensure secrets management (HashiCorp Vault, AWS Secrets Manager), and automate policy enforcement via infrastructure-as-code (Terraform, CloudFormation).
  • Perform threat modeling and data-focused risk assessments to identify sensitive data flows, quantify impact, and propose pragmatic mitigation strategies for databases, ETL jobs, streaming pipelines, and BI tools.
  • Lead data security incident response: triage data exposure events, run forensic analysis, coordinate containment and remediation, prepare post-incident reports, and implement preventive controls to avoid recurrence.
  • Design and operationalize data classification, data labeling, and metadata tagging frameworks; collaborate with data governance and product teams to ensure consistent classification across data stores and pipelines.
  • Implement tokenization, masking, and anonymization techniques for PII/PHI to enable safe analytics and development environments while maintaining utility for data science and business reporting.
  • Deploy and maintain SIEM/monitoring and alerting for data access anomalies and suspicious queries (Splunk, Datadog, Elastic, Sumo Logic), create detection rules, and escalate incidents to SOC and engineering teams.
  • Secure data warehouses and big data technologies (Snowflake security features, BigQuery IAM, Redshift encryption, Hive/Hadoop configurations), harden cluster configurations, and manage encryption keys and network segmentation.
  • Develop and execute vulnerability scanning and remediation processes for data-related infrastructure, databases, and services, collaborating with SRE and platform teams to prioritize fixes based on data sensitivity.
  • Implement secure onboarding and deprovisioning processes for data consumers, automate access workflows, and maintain audit-ready access logs to support compliance and internal audits.
  • Collaborate with product and engineering teams to embed "privacy by design" and "security by design" principles into product requirements, data models, and feature launches.
  • Manage and automate data retention, deletion, and archival policies to satisfy legal and regulatory requirements and minimize attack surface for stale sensitive data.
  • Author and maintain security runbooks, playbooks, and operational runbooks for common data security scenarios (data leak, compromised credentials, misconfigured storage buckets).
  • Conduct security code reviews and pipeline reviews for data transformation jobs (Spark, SQL, Python), flagging risky constructs and recommending secure design patterns.
  • Operate and extend secrets management and PKI infrastructure for applications and data services, including certificate issuance, rotation, and revocation processes.
  • Support external and internal audits (SOC 2, ISO 27001, HIPAA, PCI, GDPR) by preparing evidence, responding to auditor inquiries, and implementing remediation plans tied to audit findings.
  • Provide hands-on technical leadership for proactive threat hunting specific to data platforms, identifying anomalous queries, lateral movement, or exfiltration attempts and implementing mitigations.
  • Collaborate with legal and privacy teams on data subject access requests (DSARs), data residency issues, cross-border transfers, and lawful access processes, ensuring technical feasibility and compliance.
  • Build SDKs, automation scripts, and tooling to make secure data access patterns frictionless for developers and analysts while preserving controls and auditability.
  • Measure and report on data security posture and KPIs (time to detect, time to remediate, number of over-privileged accounts, DLP incidents), and present findings to technical and executive stakeholders to drive continuous improvement.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Mentor junior engineers and run internal training on secure data handling and privacy-aware analytics.

Required Skills & Competencies

Hard Skills (Technical)

  • Deep expertise in data protection technologies: encryption, tokenization, masking, anonymization, and format-preserving encryption.
  • Practical experience with cloud provider security and data services: AWS (S3, KMS, IAM, Glue, Redshift), GCP (BigQuery, KMS, IAM), and Azure (Data Lake, Key Vault).
  • Strong knowledge of database and data warehouse security: Snowflake object-level access, BigQuery IAM, Redshift VPC and encryption best practices.
  • Hands-on experience with data streaming and processing security: Kafka, Spark, Flink, secure connectors, and schema registries.
  • Familiarity with Identity & Access Management (IAM), RBAC/ABAC models, SSO/SAML/OAuth/OpenID Connect, SCIM provisioning.
  • Experience implementing DLP solutions and tuning detection rules across cloud storage, email, and endpoints (Cloud DLP, Symantec, Microsoft Purview).
  • Proficiency in scripting and automation: Python, Bash, SQL; infrastructure-as-code (Terraform, CloudFormation) to codify security controls.
  • Knowledge of secrets management and PKI: HashiCorp Vault, AWS Secrets Manager, certificate management and rotation.
  • Experience with SIEM, logging, monitoring and alerting platforms: Splunk, Datadog, Elastic, Prometheus, and creating data security detection rules.
  • Familiarity with regulatory/compliance frameworks: GDPR, HIPAA, SOC 2, PCI-DSS, ISO 27001 and how they apply to data controls.
  • Threat modeling, risk assessment, security architecture design for data platforms and pipelines.
  • CI/CD security integration: code scanning, policy-as-code, automated checks for data handling, and secure deployment practices.
  • Tools/Platforms familiarity: Snowflake, BigQuery, Redshift, Kafka, Hadoop/Spark, GitHub/GitLab, Jenkins, Kubernetes container security.
  • Experience with forensic analysis and incident response for data breaches and data exfiltration scenarios.
  • Ability to design and implement monitoring and telemetry that supports auditability, forensics, and compliance evidence.

Soft Skills

  • Strong communicator who can translate technical security requirements to product and business stakeholders.
  • Collaborative cross-functional partner: able to influence without authority and drive remediation across teams.
  • Analytical mindset with a pragmatic, risk-based approach to prioritization and control selection.
  • Mentorship and coaching: develop security knowledge across engineering and analytics teams.
  • High attention to detail and documentation discipline to maintain audit-ready processes.
  • Comfortable working in agile, fast-paced environments and handling ambiguity.
  • Customer-oriented service mentality: enable secure access for analytics while maintaining safety and compliance.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Information Security, Cybersecurity, Computer Engineering, or related technical field (or equivalent practical experience).

Preferred Education:

  • Master's degree in Cybersecurity, Information Systems, Computer Science, or related field.
  • Relevant professional certifications: CISSP, CISM, CCSP, GIAC (GCIH/GSEC/GDPR), AWS/GCP/Azure security certs.

Relevant Fields of Study:

  • Computer Science
  • Information Security / Cybersecurity
  • Software Engineering
  • Information Systems
  • Mathematics / Applied Cryptography

Experience Requirements

Typical Experience Range: 3 - 7 years in security, cloud, or data engineering roles with at least 2+ years focused on data protection or data infrastructure security.

Preferred:

  • 5+ years building and operating security controls for data platforms at scale.
  • Demonstrated experience securing cloud-native data warehouses (Snowflake, BigQuery), streaming platforms (Kafka), and building automated, auditable access controls.
  • Prior exposure to security incidents involving data, and hands-on experience leading detection and remediation.
  • Experience working with compliance teams and supporting SOC 2, HIPAA, GDPR, or ISO audits.
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