29 days ago
Austin, TX, USAMid Level
Base Salary
$104k - $135k/yr
Responsibilities
- Design, build, and improve scalable, reliable, and performant data systems.
- Build and operate real-time and batch data pipelines using Databricks, Spark, AWS services, and Terraform.
- Prepare, transform, and serve data through customer-facing stores including RDS, Elasticsearch, and DynamoDB.
- Optimize the cost and performance of data ingestion, transformation, and storage workflows.
- Provide on-call support for diagnosing and remediating production data pipeline failures.
- Evaluate tooling for data processing, ML/AI data workflows, observability, and monitoring.
- Contribute to architecture, technical design, code reviews, documentation, and engineering best practices.
- Resolve complex production issues involving data quality, performance, security, and reliability.
- Own complex data engineering initiatives from design and development through deployment and production support.
- Collaborate with Product Management, SpyCloud Labs, and Engineering on technical solutions.
Requirements
- 5+ years of professional experience in data engineering, software engineering, or a closely related discipline.
- Experience building and operating Lakehouse, Databricks, or large-scale distributed data architectures in AWS.
- Strong understanding of distributed systems for data storage, processing, and computing.
- Experience building and managing Elasticsearch or 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 Python development skills 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.
- Ability to independently own complex technical projects and contribute to architectural decisions.
- Strong communication and collaboration skills across technical and non-technical stakeholders.
- Nice-to-have familiarity with SageMaker, LangChain, vector databases, observability tools, data governance, privacy, and compliance in AI/ML environments.
- Nice-to-have experience with Go or C and cybersecurity or security-related datasets and technologies.
- A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related STEM field is preferred.
Benefits
- U.S. full-time employees receive a 401(k) with employer contribution, health, vision, and dental insurance, an HSA with employer contribution, employer-paid life and disability insurance, generous PTO, and 16 paid holidays.
- U.K. full-time employees receive a retirement savings plan with employer contribution, private health insurance, healthcare cashplan, employer-paid life and other protection benefits, an employee assistance program, 25 days of annual holiday, 8 paid bank holidays, and a paid winter shutdown.
- The role offers flexible and remote-friendly work options and access to SpyCloud’s workspace in South Austin.
- The position is a full-time employee role; benefits vary by location.
Tech Stack
Categories
Data Engineering
About SpyCloud
SpyCloud builds identity threat protection and account takeover prevention products that use recaptured criminal-market data to help enterprises and government agencies detect compromised identities and remediate risk. The privately held company, founded in 2016 and headquartered in Austin, Texas, sells subscription-based software and data services that also power dark web monitoring and identity theft protection offerings. Customers include seven of the Fortune 10.