Data Engineer
Design, build, and maintain scalable ETL/ELT pipelines and datasets in Databricks using Python, Spark, and SQL. Troubleshoot and optimize data integration processes while supporting existing SQL Server, SSIS, and SSRS solutions.
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Design, build, and maintain scalable ETL/ELT pipelines and datasets in Databricks using Python, Spark, and SQL. Troubleshoot and optimize data integration processes while supporting existing SQL Server, SSIS, and SSRS solutions.
Design, build, and maintain scalable data pipelines and ETL/ELT processes to support critical healthcare analytics within the Department of Veterans Affairs. Collaborate with stakeholders to harmonize datasets and ensure accurate, deduplicated data across enterprise systems.
The Data Engineer will design, develop, and implement scalable data pipelines and ETL workflows to support enterprise analytics. They will collaborate with stakeholders to transform raw data into reusable assets while establishing best practices for data quality and system architecture.
The Data Engineer will build and maintain data platforms to provide timely, accurate data for operational teams and business stakeholders. They will also collaborate with data scientists and DevOps teams to deploy pipelines, optimize transformations, and implement infrastructure as code.
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Design, build, and maintain reliable data pipelines and ingestion processes for the analytics platform. Collaborate with engineering and product teams to define data structures and ensure data quality across the platform.
The Data Engineer will design, build, and maintain scalable data pipelines and platforms to support analytics, AI, and operational decision-making. They will collaborate with cross-functional teams to ensure data reliability, quality, and accessibility across cloud-based environments.
The Healthcare Data Implementation Engineer serves as a subject matter expert to validate, interpret, and operationalize complex healthcare and EMR data for new client implementations. This role involves direct client interaction to troubleshoot issues, ensure data integrity, and support Azure-based data integrations.
You will develop and optimize data pipelines and data lakes on cloud platforms to support advanced analytics and machine learning models. You will also collaborate with cross-functional teams to ensure data solutions align with business needs while maintaining strict security and regulatory compliance.
The Data Engineer will build and operate a central data platform to support program impact measurement and data-informed decision-making. This role involves developing ELT pipelines, ensuring data quality, and creating self-service reporting solutions for staff and affiliates.
The data engineer will perform record linkage and entity resolution to clean and enrich commercial customer data for a municipal water utility. The role involves profiling source datasets, standardizing addresses, and producing comprehensive technical documentation including data dictionaries and methodology summaries.
You will design, build, and operationalize complex data solutions while supporting customers with their data engineering needs. Additionally, you will collaborate across teams to perform system analysis, resolve defects, and educate end users on data products.
The Data Engineer will build and maintain scalable data pipelines and ETL/ELT workflows to support enterprise analytics. They will also contribute to data modeling and governance, ensuring high-quality, production-ready data assets.
The Data Engineer will design and build scalable data pipelines, models, and APIs to support analytics and personalization initiatives. They will collaborate with Agile teams to deliver data products and mentor peers on technical standards and best practices.
You will design, build, and maintain scalable end-to-end data pipelines and ETL/ELT workflows. Additionally, you will collaborate with stakeholders to ensure data quality and implement robust data models for analytics.
The Data Engineer is responsible for architecting, developing, and maintaining scalable data infrastructure and ETL/ELT pipelines. They will also implement data quality frameworks and manage semantic layers to ensure data accessibility for analytics and reporting.
You will design, develop, and maintain high-scale ETL/ELT pipelines using Spark and Scala on AWS to support the company's data intelligence platform. Additionally, you will tune multi-terabyte Spark applications, monitor pipeline health, and integrate generative AI tools to enhance engineering productivity.
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The Data Engineer will design, create, and maintain automated ETL frameworks and data pipelines to support strategic insights. They will collaborate with cross-functional teams to implement data solutions and ensure data quality through validation and cleansing.
Design, build, and maintain scalable end-to-end data pipelines while developing efficient data processing and transformation workflows. Collaborate with cross-functional teams to integrate diverse data sources and implement robust data quality and monitoring processes.
Design, build, and maintain scalable ETL/ELT pipelines using Azure-native tools and Databricks to support federal health programs. Collaborate with stakeholders to optimize database performance, ensure data integrity, and implement automated data quality monitoring.
Design and implement scalable data pipelines, warehouses, and lakes on GCP to support supply chain and real estate operations. Collaborate with AI/ML teams to build infrastructure for RAG, copilots, and predictive analytics.
The Data Engineer designs, builds, and maintains cloud-native data platforms and integration pipelines within Microsoft Azure. This role ensures secure and reliable data exchange between internal applications, external partners, and analytics systems.
Design, develop, and maintain scalable, production-ready data pipelines using Spark, Python, and SQL in a Databricks environment. Integrate and transform diverse health and mission datasets into reliable, reusable data products while collaborating with stakeholders to solve technical challenges.
Design and implement star schema dimensional models and optimize data operations using SQL Server and ETL scripting. Deploy application code and analytical models using CI/CD tools while providing ongoing support for data applications.
The Data Engineer will lead the implementation of complex data ingestion pipelines using PySpark, Databricks, and AWS services. They will also provide technical guidance, apply engineering standards, and collaborate with cross-functional teams to deliver integrated solutions.
The Data Engineer will design, develop, and deploy a scalable modern data stack while partnering with cross-functional teams to meet business requirements. They will also establish data governance, security procedures, and foster a data-driven culture within the organization.
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You will design, build, and maintain robust data pipelines for ingestion, transformation, and orchestration to support AI and analytics applications. You will also collaborate with ML/AI teams to develop retrieval pipelines and ensure data reliability, scalability, and compliance.
The Data Engineer will design, build, and maintain robust data pipelines and infrastructure to support business operations. They will also collaborate across disciplines to modernize systems and mentor technical staff on data engineering initiatives.
The Data Engineer will build and maintain data pipelines, marts, and materialized views within an AWS-hosted Data Lake environment. They will also monitor infrastructure health and collaborate with stakeholders to support data-driven initiatives and federal compliance requirements.
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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