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As a Senior QA Automation Engineer, you will perform Quality Assurance and Automation testing for data warehouse implementations, ensuring data accuracy, completeness, and adherence to quality standards.
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In this role, the Data Engineer will be a member of the RISC team and will be a design, develop, and maintain scalable and efficient data pipelines for extracting, transforming, and loading (ETL) data from various sources into our data warehouse leveraging AWS, Databricks, Python and SQL technologies.
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10+ years of professional experience in data infrastructure (including data warehousing, ETL processes, and scalable data architectures), data engineering, and/or data science roles, with a focus on HR data.
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Knowledge of data management capabilities (data governance, data quality, metadata management, master data management, data lifecycle management and data lineage.
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Implement data quality and validation processes to ensure accuracy and consistency of data. Insight Global is seeking a Lead Data Engineer to sit remote (EAST COAST) for a large retail client headquartered in the greater Pittsburgh area.
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Design and implement modern solutions for data processing, storage and analysis, including real-time streaming, batch ETL, data lake, data warehouse, lakehouse, mesh, etc. The modern data platform is an integrated ecosystem of technology that supports traditional batch ETL, real-time data streaming, data transformation, and workload-specific storage.
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Maintain ETL data processes supporting HEDIS and other clinical quality reporting efforts. In this role you will process and analyze data to support Blue Shield of California Clinical Quality goals including HEDIS, MEDICARE STARS, MCAS measures, etc.
$96,800 - $145,200 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Drive consensus on business and technical data strategy decisions and ensure that appropriate resources are employed to deliver high quality results. Strong knowledge of leading data platforms such as Azure Data Fabric, Apache Spark, Kafka, Databricks, etc.
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Stay updated on industry trends and best practices in data engineering to continuously improve our data infrastructure. Data Governance experience. as a data engineer. Assemble large, complex sets of data that meet non-functional and functional business requirements.
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ETL/ELT, Data Pipeline and Data Science Workbench (AWS Glue, EMR, Athena) Data Governance and Data Quality Management (AWS Glue Catalog) Job Title: AWS Solutions Architect (ETL/Data Governance/AWS Glue.
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Experience in Oracle PL/SQL, Shell Scripting, ETL tools like Informatica Power Center, IDMC, MS Azure, etc. Execute Workflows, Scripts, PL/SQL packages/procedures to process data. Write database queries to analyze and validate data.
$116,000 - $145,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Ensure data quality, integrity, and consistency throughout the ETL pipeline. Your expertise in Python, PySpark, ETL processes, CI/CD (Jenkins or GitHub), and experience with both streaming and batch workflows will be essential in ensuring the efficient flow and processing of data to support our clients.
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Identify, design and implement internal process improvements including re-design infrastructure for greater scalability, optimize data delivery, and automating manual processes. Optimize and troubleshoot existing data pipelines for performance and reliability.
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Work closely with data scientists, analysts, and other stakeholders to understand data use cases and provide the necessary infrastructure and support. Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.
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We are looking for a Data Engineer with Python expertise to develop and implement: ETL pipelines, data quality reporting, and pipeline monitoring resources for data ingestion and delivery of our proprietary data sets and machine learning outputs.
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