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Salary: USD 104,000 - 135,000 / annual
SpyCloud is a cybersecurity company on a mission to disrupt the criminal underground and make the internet safer by protecting more than 4 billion accounts worldwide. This Data Engineer II role is a hands-on individual contributor position on the Engineering team, reporting to the Senior Director of Data Engineering.
You will own complex data engineering initiatives focused on evolving SpyCloud's data platform using Databricks, Spark, and AWS technologies. Your responsibilities include designing and building scalable data systems with emphasis on performance and reliability; using Databricks and Spark to prepare, transform, and serve high-quality data to customers and downstream systems; building, optimizing, and maintaining real-time and batch data pipelines using AWS services (Lambda, S3, DynamoDB, ECS, EKS) and Terraform; identifying and implementing improvements to cost and performance of data workflows; providing on-call support for troubleshooting and remediating pipeline failures outside business hours; partnering with Product Management, SpyCloud Labs, and Engineering teams to develop technical solutions; evaluating and implementing modern tooling for data processing, ML/AI workflows, and observability; contributing to architectural and technical design decisions; promoting engineering best practices through collaboration, code reviews, and documentation; identifying and resolving complex data quality, performance, security, and reliability issues in production; and independently owning initiatives from design through deployment and production support.
The role offers a flexible, remote-friendly work environment with an engaging workspace in South Austin. SpyCloud is backed by a mission-driven culture focused on preventing cybercrime, with over 250 cybersecurity experts and customers including 7 of the Fortune 10.
REQUIREMENTS:
- 5+ years of professional experience in data engineering, software engineering, or closely related discipline
- Experience building and operating Lakehouse, Databricks, or large-scale distributed data architectures in AWS
- Strong understanding of distributed systems as they relate to data storage, processing, and computing
- Experience building and managing Elasticsearch/OpenSearch data stores
- Hands-on experience designing, building, and maintaining ETL and data-processing pipelines
- Experience preparing and managing data for machine learning and LLM workflows
- Strong development skills in Python, particularly for data-intensive systems
- Practical experience with DynamoDB and other AWS-native data services
- Experience with infrastructure-as-code tools such as Terraform
- Experience troubleshooting complex data pipeline, performance, and data quality issues in production environments
- Ability to independently own complex technical projects from design through deployment and production support
- Ability to evaluate technical trade-offs and contribute to architectural and design decisions
- Strong communication and collaboration skills across technical and non-technical stakeholders
NICE TO HAVE:
- Familiarity with AI/ML tools and technologies (SageMaker, LangChain, vector databases)
- Understanding of data governance, privacy, and compliance in AI/ML environments
- Experience with observability and monitoring tools for large-scale data platforms
- Experience with Go or C programming languages
- Experience with cybersecurity or security-related datasets and technologies
- Comfort in fast-paced environments with evolving requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or related STEM field
