Data Engineer
Design, build, and maintain large-scale data warehouses and ETL pipelines to support data-driven decision-making. Integrate AI/ML models with data systems and collaborate with cross-functional teams to deliver robust data solutions.
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Design, build, and maintain large-scale data warehouses and ETL pipelines to support data-driven decision-making. Integrate AI/ML models with data systems and collaborate with cross-functional teams to deliver robust data solutions.
The Data Engineer will develop and maintain custom integrations and ETL processes while designing and optimizing scalable data pipelines. They will also collaborate with stakeholders to ensure data accuracy and provide technical support for school operations.
The role involves developing and maintaining secure, scalable data pipelines and platform services within the AWS and Databricks ecosystem. Responsibilities include supporting enterprise data ingestion, transformation, and implementing data governance controls using tools like Unity Catalog.
The Data Engineer will architect low-latency, real-time analytics systems and build new sports betting data products. They will also support production systems, triage issues during live sporting events, and integrate complex datasets into enterprise-grade APIs.
Design, develop, and maintain scalable cloud-native ETL/ELT pipelines to support healthcare analytics and regulatory reporting. Collaborate with cross-functional teams to optimize data schemas and implement rigorous data quality and validation checks.
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Design, build, and optimize scalable data pipelines and infrastructure to support AI/ML features and healthcare data processing. Collaborate with ML engineers and data scientists to ensure high-quality datasets for model training and production inference.
The role involves designing and implementing scalable data solutions and building robust data pipelines using APIs. The engineer will optimize data workflows and handle large-scale datasets within the e-commerce industry.
Architect and build low-latency, real-time analytics systems and sports betting data products. Support production systems and develop enterprise-grade APIs for predictive analytics delivery.
Develop, optimize, and maintain SQL-based data solutions and pipelines within a healthcare environment. Collaborate with stakeholders to translate data requirements into technical specifications and ensure data integrity before production.
Design and optimize enterprise-scale data solutions and reusable workflows within Snowflake and Azure environments. Build scalable ETL pipelines and implement data governance and compliance policies to ensure data quality.
Build and manage scalable enterprise data infrastructure and ingestion pipelines for contract and procurement data. Collaborate with AI and product teams to provision datasets that power autonomous negotiation agents.
Design, develop, and maintain scalable enterprise data pipelines to support advanced fraud analytics. Manage the ingestion, transformation, and optimization of structured and unstructured data across cloud platforms.
Design and maintain scalable ETL/ELT pipelines and data warehouse architecture to support data-driven decision-making. Partner with cross-functional teams to define KPIs and build analytics dashboards for executive leadership.
Own the data plane by building ingestion pipelines and transformation layers to turn messy insurance data into clean datasets. Model and tune data across Postgres and ClickHouse to power analytics and AI products.
Design and build scalable data pipelines and models to create a digital twin of Nscale's operational signals. Develop trusted datasets and metrics to enable self-serve analytics for capacity planning, cost optimization, and customer reporting.
Responsible for managing and extending BigQuery data pipelines to extract meaningful signals from large, inconsistent geospatial and device datasets. The role involves owning pipelines end-to-end and creating web-based dashboards for data visibility.
Build and maintain data ingestion pipelines and dbt models within a Snowflake warehouse on AWS. Collaborate with BI teams to translate needs into reliable data engineering work and manage operational on-call responsibilities.
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Design and implement scalable data workflows, pipelines, and streaming technologies on Kubernetes and AWS. Ensure the reliability, security, and compliance of the data layer in accordance with DoD regulations.
Architect and maintain scalable ELT pipelines using Snowflake and dbt to provide clean data for analysts and scientists. Act as a technical lead by defining best practices, conducting code reviews, and mentoring junior engineers.
Design, develop, and maintain ELT pipelines and data models to ensure data integrity within the warehouse. Collaborate with cross-functional teams to translate business requirements into scalable analytical solutions and actionable insights.
Design and implement scalable data architecture and ETL solutions to integrate data from various sources into on-prem and cloud platforms. Provide technical leadership and support for analytics systems while collaborating with stakeholders to define business requirements.
Architect and optimize daily ingestion pipelines for over 14 million listings while scaling AWS RDS PostgreSQL and Aurora databases. You will design robust ETL processes and build monitoring tools to ensure the reliability and speed of the data infrastructure.
The Data Engineer will support the scaling of Stord's commerce-enablement technology and fulfillment services. They will help manage data across OMS, Pre- and Post-Purchase, and WMS platforms to improve consumer experiences.
Design and build data infrastructure, including ETL/ELT pipelines and cloud data warehouses using the Microsoft Azure stack. Develop and optimize T-SQL scripts and stored procedures while supporting data quality and governance initiatives.
Design and implement data pipelines and validation frameworks to ensure data integrity and quality. Develop a web-based decision-support application using Dash and Mantine to allow stakeholders to monitor and act on data issues.
Build and maintain scalable data pipelines to ingest and process data while applying business logic using various programming languages. Collaborate with cross-functional teams to design data solutions and ensure data quality through rigorous validation and monitoring.
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Design and develop scalable data pipelines while making critical data modeling and schema design decisions. Collaborate with a high-output team to maintain code quality and contribute to the development of the ScreenSolve product.
The Data Engineer will design, develop, and maintain scalable ETL pipelines and data workflows to ingest and transform data into modern cloud platforms, primarily utilizing Azure Databricks and lakehouse architectures.
The Machine Learning Data Engineer will build and operate large-scale data systems to support AI training and evaluation pipelines. This role focuses on data ingestion, transformation, quality assurance, and the high-throughput delivery of data to training jobs.
The AI Data Engineer will build and operate large-scale data systems to support AI training and evaluation pipelines. Responsibilities include managing data ingestion, transformation, quality assurance, and high-throughput delivery for diverse AI workloads.
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