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Build and run pipelines that turn raw, messy healthcare data into clean, trusted, usable information. Power customer products, internal analytics, and the AI models behind our next wave of diagnostics. Design and operate ingestion, transformation, and replication pipelines on GCP.
Join a dynamic Managed Services team as a Data Architect, delivering architecture, support, and optimization for client data platforms. In this role, you will design and implement advanced data solutions, including data lakes, warehouses, and analytics pipelines. The role demands both deep technical expertise and strong consulting skills to drive client success, working in a fast-paced, remote-friendly environment alongside highly skilled professionals.
The ClickPipes Platform plays a critical role in driving the growth of the company by seamlessly onboarding and integrating data from diverse data sources into ClickHouse. As a backend engineer, you will develop and enhance integrations with various data sources, improve systems based on operational metrics, and contribute to architectural decisions. You will participate in on-call rotations to ensure system reliability.
The Billing Data Analyst will analyze financial performance, billing behavior, risk trends, and support operations. This role helps drive decision-making, reduce financial risks, and improve billing efficiency across products. The role combines analytical rigor, statistical thinking, and cross-functional collaboration to improve billing performance.
Hands-on Analytics Engineer who thrives in fast-moving, high-complexity environments and enjoys bringing clarity to ambiguity. You’ll join a growing data team with many open, high-impact challenges across billing, finance, product, GTM, and business operations. You’re someone who asks thoughtful questions, goes deep to understand how things work, and loves transforming loosely defined user problems into scalable, reliable data solutions.
Mactores is seeking a highly skilled and innovative Spark Engineer to design, develop, optimize, and operationalize high-performance data pipelines and applications using Apache Spark. This role requires hands-on expertise in distributed data processing, ETL engineering, performance tuning, and cluster management.
Lead and expand one of Zus's Data Acquisition (DA) teams, responsible for collecting health data from various sources and making it useful for the Zus platform. Build tools that interact with external health data networks to collect information and load it into Zus data stores. Develop and manage services used by customers to request data.
As a Data Scientist, you will develop machine learning algorithms, build data pipelines, and drive insights and predictive suggestions on products purchased. You will work with large amounts of data, handle data preprocessing tasks, and effectively communicate complex systems and algorithms to stakeholders.