Remote Data Jobs · Flink

Shape and evolve the backbone of Blip's real-time data processing layer. Design and implement streaming and batch data systems that move and transform information reliably and efficiently across Blip’s platform. Champion data modeling excellence, ensuring high-quality, discoverable data for real-time consumption. Key responsibilities include data engineering & pipeline architecture, modeling & storage, and reliability, quality & observability.

Shape and evolve the backbone of Blip's real-time data processing layer. Design and implement streaming and batch data systems that move and transform information reliably and efficiently across Blip’s platform. Champion data modeling excellence, ensuring high-quality, discoverable data for real-time consumption. Key responsibilities include data engineering & pipeline architecture, modeling & storage, and reliability, quality & observability.

As a Machine Learning Engineer on the Data Engineering team, you’ll partner closely with the Data Science team to build out our foundational Machine Learning platform. You will build internal tools and services to accelerate UD’s model building and deployment process. You will lead technical initiatives, and drive results in a fast-paced, dynamic environment and lead code reviews to maintain code and data quality.

Join the pricing and underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines, key elements that have a significant impact on the company’s growth. Shape the architecture of data products designed for data analytics and data science.

Design, build, and manage data warehouse to serve as the single source of truth for the organization. Develop and deploy low-latency, real-time data streaming pipelines. Enable self-service analytics by building clean, well-documented, and trusted datasets. Establish and follow data governance and security best practices. Stay current with industry best practices and emerging data analysis tools and techniques.

The Director, Data Engineering will lead Data Platform initiatives, defining the strategy, architecture, and execution of our end-to-end data ecosystem, encompassing data ingestion pipeline, operational data stores, our evolving data lakehouse, and robust data APIs. This role requires deep technical expertise and a strong understanding of how data can drive business value.

Design, maintain, and scale streaming ETL pipelines for blockchain data. Build and optimize ClickHouse data models and materialized views for high-performance analytics. Develop and maintain data exporters using orchestration tools. Implement data transformations and decoding logic. Establish and improve testing, monitoring, automation, and migration processes for pipelines. Ensure timely delivery of new data features in alignment with product goals.