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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and running distributed systems in the cloud, with a strong focus on low-latency APIs, entity resolution, and graph analytics. Proven ability to lead technical initiatives, mentor engineers, and implement privacy and security measures in production environments.
Highest-signal resume keywords
Distributed Systems EngineeringGraph AnalyticsLow-Latency API DevelopmentTechnical LeadershipCloud Infrastructure Proficiency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Entity ResolutionGraph Schema DesignBatch and Real-Time PipelinesProduction ObservabilityPerformance ImprovementQuantifiable Production-Scale ExperienceSparkKafkaFlinkJava
Soft Skills
MentoringCollaborationDocumentation
Tools & Technologies
AWSKubernetesCI/CDDatabricksSageMakerAirflowNeo4jAmazon Neptune
Industry Keywords
Fraud IntelligenceIdentity VerificationPrivacy ProtectionPII Protection
Tech Stack
Tools & technologiesAirflowAWSCloudDistributed SystemsJavaKafkaKubernetesNeo4jPythonScalaSpark
About the role
Key responsibilities & impact- Define graph schemas, relationships, and ontology for consistent, extensible identity data
- Own entity resolution at scale across records, people, devices, and addresses
- Design batch and real-time pipelines, low-latency APIs, and high-volume serving systems
- Build production systems supporting ML features, model inference, and graph analytics for fraud intelligence
- Improve performance, reliability, and cost using measurable outcomes
- Lead architecture decisions, document tradeoffs, and carry initiatives from design through production rollout
- Mentor engineers and set standards for design reviews, testing, CI/CD, and operations
- Build privacy, security, and PII protection into systems
- Collaborate across Engineering, Data Science, Product, and Security
Requirements
What you’ll need- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field
- 7+ years building and running distributed systems in the cloud, with at least 2 years at Staff or Senior Staff scope, or equivalent
- Experience owning systems end to end in production, including being on call
- Quantifiable production-scale experience, including improvements to latency, reliability, or cost
- Deep Spark, Kafka, or Flink experience in batch and streaming, including production debugging
- Experience building and tuning low-latency APIs
- Graph or entity-resolution experience; fraud or identity verification experience is a strong plus
- Proficiency with AWS, Kubernetes, infrastructure as code, CI/CD, and production observability
- Experience with ML data pipelines on Databricks, SageMaker, or similar
- Experience with Airflow or equivalent orchestration
- Technical leadership experience, including ambiguous cross-team work, mentoring engineers, and influencing system direction through design documents
- Experience or proficiency with Java, Scala, or Python; Spark, Kafka, Flink, Airflow, AWS/EMR, Neo4j, and Amazon Neptune
- Must be authorized to work in the country where the job is located
Benefits
Comp & perks- Bonus
- Equity
- Benefits
- Annual bonus or commission plan
- Hybrid work arrangement with expected office attendance 2–3 days a week where a location is available
- Accommodation support during the application or hiring process
- Equal employment opportunity and diversity commitment