HRS is a pioneer in business travel, offering a digital platform that integrates ProcureTech, TravelTech, and FinTech to transform the travel experience.
Business Unit
We are building a next‑generation, data‑driven Insurtech Claims Accommodations Platform designed to unify fragmented data ecosystems across products, geographies, and operational systems.
Position
Senior Data Engineer
Responsibilities
Design and implement a cloud‑native data warehouse on Azure Fabric and a structured data lake on OneLake; develop dimensional models for claims analytics, cost reporting, and executive dashboards.
Establish data governance policies, including data lineage, cataloguing with Purview/Glue, access controls, and PII masking for compliance.
Architect end‑to‑end ELT/ETL pipelines ingesting from claims management systems, legacy sources (ODBC/SRSS), accommodation APIs, policy engines, and hosted operational CRMs; build batch ingestion pipelines in Azure Data Factory.
Implement real‑time streaming pipelines for claims events, accommodation availability updates, and pricing signals using Azure Event Hubs, Kafka, or Flink.
Deploy dbt for modular, version‑controlled data transformation layers with automated data quality testing.
Develop and optimise CDC pipelines from operational PostgreSQL/SQL Server databases.
Build ML‑ready feature stores (e.g., AWS SageMaker Feature Store) and develop predictive models for cost forecasting, length‑of‑stay prediction, supplier risk scoring, and demand surge detection.
Implement MLOps pipelines for model training, versioning, deployment, and monitoring with MLflow and CI/CD frameworks; operationalise model outputs via REST APIs for real‑time decisioning.
Architect vector databases and build RAG pipelines over claims and policy documents to enable LLM‑powered workflows for automated claims summarisation, accommodation recommendation, and SLA breach prediction.
Build agentic AI systems that autonomously monitor pipelines, trigger re‑routing logic, and surface anomalies to adjusters.
Integrate structured and unstructured data into unified AI‑ready datasets for continuous model improvement.
Technical Requirements
Proficiency in data warehouse & lakehouse design using AWS Redshift, Azure Synapse, OneLake; expert in dimensional modelling, star schemas, and data vault for insurance domains.
Experience building production‑grade ELT/ETL and CDC pipelines with Azure Data Factory, AWS Glue, and related tools.
Deep hands‑on expertise across Azure (ADLS Gen2, Synapse, ADF, Purview) and AWS (S3, Glue, Redshift, SageMaker); ability to implement IaC with Terraform or Bicep.
Experimental skills in ML & predictive modelling (feature engineering, MLflow, scikit‑learn, XGBoost) with production deployment, monitoring, drift detection, and retraining.
Streaming & real‑time data expertise with Apache Kafka, Azure Event Hubs, Spark Structured Streaming, or Flink.
Knowledge of AI‑enabled workflows & RAG infrastructures: vector databases, LangChain/LlamaIndex, prompt engineering.
Data governance & quality skills: cataloguing, lineage (Purview/OpenLineage), PII masking, RBAC, Great Expectations/dbt tests.
Programming languages and tooling: Python (primary), SQL (advanced), Scala/Java (preferred); Git, Docker, Kubernetes; CI/CD via GitHub Actions or Azure DevOps.
Preferred Background
Experience in Insurtech, Fintech, or financial services dealing with policy, claims, underwriting, and regulatory data.
Knowledge of accommodation/travel/claims management platforms, supplier networks, booking APIs, cost structures, and SLA frameworks.
Familiarity with insurance regulatory requirements (APRA, Lloyd’s, FCA) and data sovereignty considerations.
Past green‑field data platform builds, architecting from scratch.
Fluency in English.
Perspective
Join a global network of intrapreneurs dedicated to reinventing the travel industry and delivering sustainable value through a culture of growth, ownership, and continuous improvement.
Location & Mobility
HCM City. All necessary work equipment and mobility provided.
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