Join Madhive's growing data engineering team as a Senior Data Engineer, where you'll play a crucial role in scaling the infrastructure that powers our universal pixel and transforming high-volume event data into reliable, actionable signals. You’ll work closely with cross-functional teams to build robust, scalable pipelines and models, while helping ensure high data quality across our platform.
RevenueCat is seeking a highly technical Engineering Manager to support the Data Team's growth, help create a data-driven product, mentor engineers, and contribute to technical decisions. The manager will help influence the grand vision and strategy on the Data.
As a Senior Data Engineer, you will be a core contributor to the development and maintenance of scalable, secure, and high-performance data pipelines, collaborating with product, analytics, and engineering teams to ensure reliable data availability across the organization. You'll also play a critical role in mentoring junior engineers, adhering to engineering best practices, and proactively improving our data infrastructure.
Design, build, and maintain scalable data pipelines that process high-volume, multi-source data feeds. Own end-to-end data infrastructure including pipeline orchestration, data warehousing, and OLAP systems. Provide code reviews, technical direction, and mentorship to junior team members.
We are looking for a Senior Staff Data Engineer to build commercial products and deliver reliable, scalable, and maintainable applications. You will lead projects from start to finish, collaborating with Product Managers to define requirements and implement solutions. The role focuses on simplicity and enhancing system performance, stability, and user experience, while mentoring other engineers and ensuring high-quality, testable software.
The work of a Data Engineer at the Phillies extends well beyond merely coding. As a member of our team, you will play a central role in optimizing how data flows throughout the Phillies organization — from ingestion to modeling to application. You will help design, build, and optimize the data infrastructure that powers predictive models, research, dashboards, reports, and internal applications.
Design, build, and implement generalized large-scale, sophisticated data pipelines using Nifi for downstream analytics and data science for our Sport Performance products. Design and develop scalable Nifi ingestion pipelines within AWS cloud services to consume real-time and batch data from external sources. Design and create data models for use throughout the ETL system.
Shape the future of how Wikimedia’s vast data ecosystem serves both internal teams and the global community, helping drive the Data Platform Engineering team’s effort to unify data systems across the Wikimedia Foundation to deliver scalable solutions that support internal and external platform users and the open knowledge movement.
We’re seeking an exceptional Staff Data Engineer to help take our data platform to the next level where you’ll architect and build scalable data infrastructure, empower data-driven decision-making, and help shape the future of fraud prevention. You will collaborate with data scientists, engineers, and business stakeholders to ensure high-quality, actionable data insights to enable business outcomes.
As a Data Engineer on the Insights team, you’ll be central to designing and building the data pipelines, services, and infrastructure that power our product’s AI-driven insights. You will work at the intersection of product engineering, analytics, and AI. This role is ideal for someone who loves working with structured and unstructured data.