Senior Data Engineer (Cloud)
Migrate data products and analytical workloads from legacy systems to a modern cloud data platform. Build and maintain scalable batch data pipelines while ensuring data quality and performance optimization.
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Migrate data products and analytical workloads from legacy systems to a modern cloud data platform. Build and maintain scalable batch data pipelines while ensuring data quality and performance optimization.
Design and implement scalable data solutions using Microsoft Fabric, Azure SQL, and modern data warehousing architectures. Manage end-to-end data pipelines, optimize database performance, and support AI-driven analytics initiatives.
The Sr. AWS Data Engineer will lead the modernization of a healthcare data platform by migrating XML object store data to a scalable AWS-native architecture. This role involves designing reporting layers, optimizing query performance, and collaborating with stakeholders to ensure data discoverability and usability.
The Data Engineer will build and maintain ingestion and transformation pipelines using tools like Dagster, dbt, and Snowflake. They will also collaborate with analytics and product teams to design data models and ensure production pipeline reliability.
You will lead and mentor the engineering team while ensuring high-quality project delivery for customers. Additionally, you will design, maintain, and optimize scalable data pipelines and infrastructure within the Google Cloud environment.
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The Senior Clinical Data Engineer will design, develop, and maintain scalable data pipelines to process and transform clinical and medical device data. They will collaborate with cross-functional teams to ensure data quality, consistency, and usability for statistical analysis and evidence generation.
You will own and build the large-scale data infrastructure and pipelines required to train frontier AI models. This includes designing data curation strategies and developing tooling to enable researchers to process massive datasets efficiently.
The Project Civil Engineer will lead design efforts and serve as a project manager for large-scale data center infrastructure projects. Responsibilities include preparing design documents, performing calculations, and coordinating with multidisciplinary teams and clients.
Lead the design, development, and maintenance of enterprise-scale data pipelines and foundational data assets to support analytics and AI initiatives. Establish scalable data engineering standards and collaborate with cross-functional teams to ensure data accuracy, security, and reliability.
The Senior Security Engineer will lead the data security domain by establishing strategies, standards, and controls for protecting sensitive data across its lifecycle. They will collaborate with cross-functional teams to embed security into data pipelines and automate workflows while ensuring regulatory compliance.
You will design and implement robust, production-grade data pipelines to transform raw healthcare data into trusted, queryable datasets. Additionally, you will collaborate with cross-functional teams to onboard new customers and ensure the reliability and performance of core ML and product data workflows.
The Data Engineer will design, implement, and maintain scalable data pipelines and infrastructure to transform proprietary data into reliable research-grade datasets. They will collaborate with cross-functional teams including data scientists and economists to ensure data quality and support evolving business needs.
The Solutions Engineer will design, build, and deliver enterprise-scale data engineering solutions using Microsoft Azure and Microsoft Fabric. This role involves collaborating with stakeholders to implement secure, scalable data platforms and pipelines that support analytics and AI-driven use cases.
Design, develop, and maintain scalable data platforms and pipelines using Microsoft Azure services. Collaborate with cross-functional teams to implement data ingestion, transformation, and quality frameworks that support enterprise analytics and AI initiatives.
You will design and implement scalable backend systems and data pipelines to process complex clinical datasets. This involves collaborating with AI engineers to productionize model workflows and ensuring the reliability and quality of data delivery.
You will own and evolve the core data infrastructure, including data warehouses, pipelines, and transformation layers. You will also partner with data scientists and analysts to ensure data is clean, accessible, and trustworthy for the organization.
Act as the primary technical subject matter expert for Securiti AI solutions, supporting sales teams throughout the entire sales cycle. Lead technical discussions, deliver customized product demonstrations, and execute proof-of-concepts to address customer needs in data discovery and security posture management.
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The Senior Manager of Data will lead and mentor a multi-disciplinary team of data engineers and data scientists to deliver high-quality data pipelines and actionable insights. They will define the data strategy, oversee architecture, and collaborate with stakeholders to ensure business-aligned data solutions.
You will design and develop large-scale, cloud-native, multi-tenant data services and pipelines to support healthcare provider data management. The role involves full ownership of the software development lifecycle, including planning, coding, testing, and performance optimization.
You will design and support ETL workflows to extract, transform, and load legacy healthcare data into athenahealth systems. The role involves collaborating with cross-functional teams to ensure data accuracy, consistency, and compliance with interoperability standards.
The Data Engineer II is responsible for designing, developing, and maintaining robust data pipelines, databases, and analytical frameworks to support healthcare quality initiatives. They will collaborate with cross-functional teams to transform complex healthcare data into actionable insights through reports, dashboards, and visualizations.
Design and implement data ingestion processes from various sources including databases, APIs, and files. Manage the full data lifecycle, including data modeling, quality assurance, and the development of ETL/ELT pipelines within the Azure and Microsoft Fabric ecosystem.
You will act as the senior technical authority for complex data and analytics engagements, owning end-to-end solution architecture and delivery. You will lead client discovery, define technical standards, and coach senior consultants to ensure architectural integrity and business success.
You will own the full lifecycle of data products, collaborating with Data Scientists to bring real-time pricing algorithms to production. Additionally, you will architect data pipelines, manage infrastructure, and lead cross-team efforts to scale machine learning solutions.
The Senior Data Engineer will manage and optimize SQL databases while ensuring high performance, security, and availability. They will also lead daily standups, prioritize tasks, and mentor team members to align data solutions with business objectives.
The Senior Data Engineer will own the end-to-end data substrate, including ingestion, modeling, and governance within a Databricks and Azure environment. They will build and maintain serving layers for AI agents while ensuring data quality, performance, and cost-efficiency through automated infrastructure and monitoring.
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Lead the design and implementation of large-scale, reliable data pipelines while mentoring junior engineers to raise team standards. Collaborate with cross-functional stakeholders to ensure data products are performant, compliant, and trustworthy.
Design, develop, and ship high-quality technical solutions while providing leadership and mentorship to the engineering team. Advocate for system health, participate in on-call rotations, and collaborate with cross-functional teams to drive product goals.
Design and build scalable, cloud-native data platforms while mentoring other engineers to foster a culture of continuous improvement. Create robust ETL/ELT pipelines and support data governance efforts to ensure data quality and lineage.
Design and build scalable, cloud-native data platforms while mentoring other engineers to foster a culture of continuous improvement. Develop robust ETL/ELT pipelines and ensure data governance, lineage, and quality across the platform.
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