2 months ago
Base Salary
$140k - $210k/yr
Responsibilities
- Own complex features and technical improvements from discovery through production rollout across backend services and data-processing pipelines.
- Design and operate Java, Spring Boot, and Maven services supporting APIs, asynchronous workflows, reporting, aggregation, export, and scheduling.
- Build and maintain Python and PySpark ingestion and transformation pipelines using Azure Databricks and Delta Lake across batch and streaming workloads.
- Develop event-driven functionality with Kafka and improve service performance, scalability, fault tolerance, concurrency, caching, and failure recovery.
- Optimize Spark joins, partitioning, Delta operations, cluster utilization, and query performance while maintaining data quality and tenant isolation.
- Build observability with metrics, logs, traces, dashboards, monitors, and alerts using Datadog, Grafana, OpenTelemetry, Prometheus, and Micrometer.
- Participate in on-call and incident-response workflows, reduce alert noise and operational toil, and implement sustainable corrective actions.
- Review designs and code, document technical decisions, collaborate across teams, and use AI-assisted engineering tools while maintaining production quality.
Requirements
- 8+ years of experience building and operating production software systems as a highly autonomous individual contributor.
- Strong proficiency in Java and Spring Boot, including distributed systems and microservices design and operation.
- Production experience with asynchronous or event-driven systems, preferably Apache Kafka.
- Strong experience with Python, PySpark, Apache Spark, Delta Lake, and Azure Databricks or a comparable managed Spark platform.
- Hands-on experience with test-driven development, automated testing strategies, and quality gates.
- Strong understanding of metrics, logs, distributed tracing, dashboards, monitoring, and alerting, including Datadog and Grafana.
- Experience responding to PagerDuty incidents, Datadog alerts, or equivalent production alerting workflows, plus willingness to participate in on-call rotation.
- Experience using AI engineering tools such as Devin, Claude, or similar systems to produce production-ready code, tests, documentation, and operational improvements.
- Ability to independently diagnose complex performance and reliability problems and clearly communicate architecture, implementation decisions, and trade-offs.
- Preferred experience includes batch and streaming pipelines, Databricks SQL, Databricks SDKs, Delta operations, schema migrations, Azure Blob Storage, Azure Identity, Azure Key Vault, Kubernetes, containers, CI/CD, infrastructure as code, service-level indicators and objectives, error budgets, data governance, encryption, auditability, tenant isolation, and incremental system modernization.
Benefits
- Comprehensive healthcare coverage, flexible PTO, equity RSUs, annual performance bonus opportunities, retirement account support, 14+ weeks of paid parental leave, career development opportunities, and company-paid privacy certification exam fees.
- Office-first culture encouraging three days per week in the office for most roles, with role-specific flexibility to be confirmed with the recruiter.
- Benefits vary by country and the role may also be eligible for discretionary bonuses, equity, and/or commissions.
Tech Stack
Categories
BackendData Engineering
About OneTrust
OneTrust builds an enterprise data governance and compliance platform used to manage privacy, consent, and AI governance across global operations. Its products span privacy impact assessment and data‑mapping automation, cookie and consent management, vendor risk, subject access requests, incident management, and policy enforcement, sold as subscription software. Founded in 2016 and headquartered in Atlanta, the privately held company serves thousands of organizations worldwide across regulated industries.