Data Engineer

Company Overview: Dune Security’s User Adaptive Risk Management solution proactively prevents insider threats and social engineering by simulating multi-channel attacks, scoring user risk, and adapting training and controls in real time. Powered by AI, we quantify employee risk with comprehensive data and automatically deliver user‑adaptive training and intervention. For higher‑risk users, our platform integrates seamlessly with the broader security stack to dynamically implement controls.

Backed by Craft Ventures, Toba Capital, Alumni Ventures, Fire streak Ventures, and Antler, we empower CISOs to proactively manage human risk—the leading cause of cybersecurity breaches—and build safer, more resilient organizations.

Role Overview

Dune Security is seeking a Data Engineer to design and scale the data infrastructure that powers our real‑time cybersecurity platform. In this role, you’ll help build and maintain secure, reliable data pipelines and storage systems that enable adaptive risk modelling, AI‑powered insights, and seamless integrations. Reporting directly to the VP of Engineering, you’ll join a high‑impact team driving core engineering decisions at the intersection of security, data, and enterprise operations.

You’ll play a key role in powering the data infrastructure that drives Dune’s user‑adaptive risk modelling, enabling proactive defence against insider threats and social engineering across global enterprises.

Key Responsibilities

• Propose and execute an SLA/SLO of 99.95%+, data and signal strategies for storage, retrieval, visualisation, and utilisation of data for business and technical objectives.
• Design and implement robust ETL/ELT and AI/ML pipelines for both batch and streaming data, using orchestration tools like Airflow, Dagster, or Prefect.
• Develop and optimise cloud‑based data lakes and warehouses (e.g., S3, Delta Lake, Snowflake, Big Query) for telemetry, user behaviour, and system logs.
• Build secure, scalable data integrations with internal microservices and external platforms (SIEMs, IDPs, ITSM tools) using REST, GraphQL, and SCIM APIs.
• Ensure data reliability, observability, and compliance by implementing data validation, schema enforcement, monitoring, and access controls.
• Build real‑time data
  , business, technical analytics dashboards, and streaming infrastructure.
• Build pre‑processed, sync, async, plaintext versus encrypted data features used for high QPS, low latency secure analysis.
• Collaborate closely with backend, integration, and ML engineers to align data architecture with platform goals, risk models, and customer insights.
• Contribute to infrastructure‑as‑code practices using Terraform and CI/CD pipelines for data environments and new AI approaches.
• Maintain and evolve RBAC/ABAC controls
  , data masking/tokenisation pipelines, and audit trails in accordance with frameworks like SOC 2, GDPR, and CCPA.
• Document data flows, transformations, and architecture to support internal cross‑functional teams and external compliance.
• Stay current with data engineering trends to bring innovation in scalability, performance, and security. Evaluate new tools and technology.

Qualifications

Required:

• BS degree in Computer Science, Engineering or equivalent.
• 3–6 years of experience in data engineering, backend engineering, or similar roles.
• Proficiency in Python, Go, SQL languages and distributed technology in Cloud, Spark, Flink, Redis, Kafka, Kinesis, Pulsar, Beam, Snowflake, Big Query, Redshift, Databricks, Terraform or equivalent.
• Experience designing and operating cloud‑native data storage solutions (e.g., S3, Snowflake, Delta Lake), data warehouses, and data lakes.
• Hands‑on experience with data orchestration tools (e.g., Airflow, Prefect, Dagster), microservices software architecture and engineering (e.g. Docker, Mesh, etc.).
• Strong understanding of data security, governance, and compliance best practices.
• Proven ability to design and scale reliable ETL/ELT workflows.
• Comfortable working with APIs (REST, GraphQL), secrets management, and cloud infra (preferably AWS).
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Preferred:

• Ph.D. or Masters in Computer Science,…