Job ID: JOB_ID_2721
Role Overview
We are currently seeking a highly skilled and motivated Quantexa Data Engineer to join our dynamic team. This is a hybrid role based in either New York City, NY, or Charlotte, NC. As a Quantexa Data Engineer, you will be at the forefront of building and scaling data-driven decision intelligence solutions. You will leverage the power of the Quantexa platform to design and implement sophisticated entity resolution, network/graph analytics, and risk detection use cases within large-scale Google Cloud Platform (GCP) data environments. This position is ideal for an engineer with a strong background in Scala or Java, Elasticsearch, and modern big data pipelines who is eager to translate complex business requirements into production-grade solutions. The successful candidate will work closely with cross-functional teams to deliver high-impact results in a fast-paced environment, ensuring that data integrity and analytical accuracy are maintained at the highest levels.
Key Responsibilities
- Design and build Quantexa solutions by implementing entity resolution (ER), matching rules, and network generation using Quantexa SDKs and configuration frameworks.
- Develop custom Quantexa scoring, models, and rules for critical financial use cases such as AML (Anti-Money Laundering), Fraud detection, KYC/CDD, credit risk, customer 360, or supply chain risk.
- Engineer robust data pipelines on GCP using BigQuery, Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Storage.
- Build CI/CD enabled data pipelines using tools like Cloud Build, Terraform, and GitHub Actions, optimizing for performance and cost efficiency.
- Optimize Elasticsearch indices for high-performance entity and network searches, ensuring resilient query patterns for high-volume workloads.
- Develop microservices and batch jobs in Scala or Java, integrating seamlessly with Quantexa APIs and SDKs.
- Implement comprehensive unit and integration tests to ensure the highest quality of code and system observability, including logging, metrics, and tracing.
- Establish data profiling, standardization, and deduplication practices to maintain data quality and governance.
- Define match/merge thresholds and survivorship strategies to ensure data integrity across the platform.
- Collaborate with InfoSec teams to ensure all solutions meet security, privacy, and compliance standards like SOC 2, ISO 27001, and specific AML/KYC regulations in financial contexts.
- Deploy and manage Quantexa components on GCP using Kubernetes (GKE) and other managed services.
- Monitor performance, troubleshoot complex pipelines, and drive continuous improvement in production operations.
Technical Requirements
- Minimum of 3 to 7+ years of professional experience in software or data engineering, with a focus on large-scale data systems.
- Proven hands-on experience with Quantexa implementation, specifically in projects involving entity resolution, scoring rules, and network/graph building.
- Strong proficiency in programming with Scala or Java, with a focus on functional patterns, collections, and concurrency.
- Extensive expertise in the Google Cloud Platform (GCP) ecosystem, including BigQuery, Dataflow/Beam, Dataproc/Spark, Pub/Sub, Cloud Storage, and Cloud Composer (Airflow).
- Deep understanding of Elasticsearch, including schema design, indexing strategies, analyzers/tokenizers, query DSL tuning, and cluster operations.
- Experience with Apache Spark (RDD/DataFrame APIs), SQL, and data modeling for analytics and graph workloads.
- Familiarity with CI/CD tools and DevOps practices such as Git, Cloud Build, GitHub Actions, Terraform, Docker, and GKE.
- Solid understanding of data quality principles, matching logic, and survivorship rules.
- Excellent communication skills and the ability to partner effectively with business stakeholders and Subject Matter Experts (SMEs).
Preferred Qualifications and Skills
- Experience within the Financial Services sector, particularly in AML, sanctions screening, fraud detection, KYC/CDD, or trade surveillance.
- Knowledge of graph technologies like Neo4j, GraphFrames, Gremlin, or NetworkX.
- Experience with streaming technologies such as Kafka or Pub/Sub for near-real-time entity resolution pipelines.
- Familiarity with observability tools like Prometheus, Grafana, Cloud Monitoring, and Cloud Logging.
- Python proficiency for data tooling, automation, and orchestration.
- Familiarity with Quantexa Workbenches, visualization tools, and case management integrations.
- Relevant certifications such as Google Cloud Professional Data Engineer, Professional Cloud Architect, or Elastic Certified Engineer.
- Quantexa training or certifications are a significant plus; employer-funded training may be provided if not already present.
Education and Certifications
Candidates should possess a Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related technical field. Professional certifications from Google Cloud or Elastic are highly regarded and will strengthen your application. We value continuous professional development and support our engineers in staying current with the latest industry trends and technologies. This role offers a unique opportunity to work with cutting-edge decision intelligence technology in a high-stakes environment.
Special Requirements
Hybrid role (NYC or Charlotte); 12-month contract; Interview: Phone and Video; Requires Passport Name, Last 4 SSN, LinkedIn ID, and DOB for submission; Working through preferred vendors.
Compensation & Location
Salary: $155,000 – $205,000 per year
Location: New York, NY
Recruiter / Company – Contact Information
Recruiter / Employer: Cambay Consulting LLC
Email: shubham.kumar@cambayllc.com
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