DNSE

46 Ngo Quyen, Hà Nội

Quy mô công ty : 100-499

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Tóm lược

DNSE

Work directly with Product Owner to architect and enhance the CRM data platform, integrating data from multiple sources including trading activities, customer touchpoints, and marketing channels.
Work directly with our Data Scientists and Investment Advisory department to build innovative product features with Machine Learning and Artificial Intelligence.
Work with stakeholders throughout the organization to catalog and collect data and identify opportunities for leveraging company data to drive business solutions.Analyze user journeys, engagement patterns, and lifecycle data to optimize campaign performance, improve user segmentation, and refine automation workflows.
Develop and maintain data synchronization pipelines between CRM, marketing platforms, and internal systems to ensure data accuracy and real-time availability.
Build and monitor dashboards and KPIs for CRM operations, marketing effectiveness, and customer satisfaction using BI tools and analytics frameworks.

Fastest growing fintech startup with state-of-the-arts technology.
Top notch engineering team.
Competitive salary with regular review and advancement.
Opportunity to take charge of your own works and directly contribute to company products.
Small, young and close-knit team. We move fast, work hard and play hard.

Strong problem-solving skills with an emphasis on product development (required).
Experience working with SQL / NoSQL database: Postgres, AWS redshift (required).
Experience working with data transformation and integration tools: Dbt, Airbyte (required).
Experience working with workflow managements: Airflow, Prefect (required).
Experience working with Hadoop ecosystem, Apache Spark, Kafka, Flink, Faust (required).
Experience working with Kubernetes, Docker, Cloud environments (preferred).
Experience working with search engines: Elasticsearch, Solr (preferred).
Experience working with Machine learning operations (MLOps) (preferred).
Experience working with Data observability (preferred).
Experience working with and creating data architectures and designing Data Warehouse (preferred).
Excellent written and verbal communication skills for coordinating across teams (preferred).
A drive to learn and master new technologies and techniques (required).