Quantexa Engineer

We’re seeking a Quantexa Engineer to build and scale data-driven decision intelligence solutions leveraging the Quantexa platform. You’ll design and implement entity resolution, network/graph analytics, and risk detection use cases across large-scale GCP data environments. The ideal candidate has hands-on engineering experience with Scala or Java, Elasticsearch, and modern big data pipelines-and can translate business requirements into production-grade Quantexa solutions. What You’ll Do

• Design & Build Quantexa Solutions

• Implement entity resolution (ER), matching rules, network generation, and contextual analytics using Quantexa SDKs and configuration frameworks.
• Develop custom Quantexa scoring, models, and rules for AML, fraud, KYC/CDD, credit risk, customer 360, or supply chain risk.

• Data Engineering on GCP

• Ingest, transform, and model large-scale datasets using BigQuery, Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Storage.
• Build CI/CD-enabled data pipelines (e.g., Cloud Build, Terraform, GitHub Actions) and optimize for performance and cost.

• Search & Retrieval

• Design and tune Elasticsearch indices for entity and network search; implement analyzers, relevance tuning, aggregations, and resilient query patterns for high QPS workloads.

• Software Engineering

• Develop microservices or batch jobs in Scala or Java, integrating Quantexa APIs/SDKs.
• Implement unit/integration tests and quality gates; ensure observability (logging, metrics, tracing).

• Data Quality & Governance

• Establish data profiling, standardization, and deduplication practices; define match/merge thresholds and survivorship strategies.
• Partner with InfoSec to meet security, privacy, and compliance requirements (e.g., SOC 2, ISO 27001; AML/KYC in FS contexts).

• Production Operations

• Deploy and operate Quantexa components on GCP (Kubernetes/GKE or managed services).
• Monitor performance, troubleshoot pipelines, and drive continuous improvement.

• 3-7+ years of software or data engineering experience (open to leveling up or down).
• Hands-on Quantexa implementation experience (projects involving ER, scoring rules, and network/graph building).
• Strong programming in Scala or Java (collections, concurrency, functional patterns preferred).
• Solid GCP big data expertise: BigQuery, Dataflow/Beam, Dataproc/Spark, Pub/Sub, Cloud Storage, Cloud Composer (or Airflow).
• Elasticsearch: schema design, indexing strategies, analyzers/tokenizers, query DSL, performance tuning, cluster ops basics.
• Experience with Spark (RDD/DataFrame APIs), SQL, and data modeling for analytics/graph workloads.
• CI/CD and DevOps fundamentals: Git, Cloud Build/GitHub Actions, Terraform (or similar), Containerization (Docker), GKE.
• Strong understanding of data quality, matching logic, and survivorship rules.
• Excellent communication skills and the ability to partner with business/SME teams.

Nice to Have

• Financial Services use cases: AML, sanctions screening, fraud, KYC/CDD, correspondent banking, trade surveillance.
• Graph technologies: Neo4j, GraphFrames, Gremlin, NetworkX.
• Streaming: Kafka / Pub/Sub * Dataflow pipelines for near-real-time ER.
• Observability: Cloud Monitoring, Cloud Logging, Prometheus/Grafana.
• Security & governance: IAM, VPC-SC, KMS, DLP tooling.
• Python for data tooling and orchestration.
• Familiarity with Quantexa Workbenches, visualization, and case management integrations.

Education / Certifications (Preferred)

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.
• Google Cloud Professional Data Engineer or Professional Cloud Architect.
• Elastic Certified Engineer (plus).
• Quantexa training/certifications (nice to have; employer-funded if not present).