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Collaborates with various functions across the organization, such as EY’s Information Security, IT Risk Management, members of the business and Service Line Quality, and Talent, to design and implement controls in order to protection confidential/personal information.
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Responsibilities include querying databases, data cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and assisting with the communication of scientific findings via peer-reviewed publications and scientific conferences.
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Databases: Oracle, MS SQL Server, Azure PostgreSQL, Denodo - SQL: design and develop complex SQL queries, stored procedures, views, or to tune existing ones for optimal performance - Programming: Python, R - Azure Cloud - Azure Databricks - ETL Tools: Azure Data Factory, IBM DataStage etc.
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Work closely with data engineers to create services that can ingest from both internal and external sources and ensure data quality and timeliness. Certificates earned in data mining, machine learning, deep learning, statistical modeling, cloud computing, and data engineering.
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The Database Coordinator II oversees and validates the data entered into the Homeless Management Information System (HMIS) and other databases by program staff and dedicated Data Quality Specialists; supports Database Lead. Conducts regular audits to ensure data accuracy, and corrects errors, ensures required monthly and periodic reporting to funder, and generates reports from HMIS data showing program performance.
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Facilitate data collection and display of clinical quality-related data for internal reports and external reports, such as HEDIS, PCMH, Health Resources and Services Administration (HRSA), Community Clinic Association of Los Angeles County (CCALAC), EMR Meaningful Use Attestation, Uniform Data System (UDS) Reporting, and other reports as needed.
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Maintain detailed documentation of your work and changes to support data quality and data governance requirements. Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams.
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Data engineering stack on cloud architectures - AWS, Azure, Google Cloud Platform (GCP) - Design, develop and productionize data engineering pipelines on a massively parallel processing (MPP) and cloud-based tech stack, utilizing solution aspects from hybrid-clouds like Microsoft Azure, Amazon Web Services (AWS), data lakes and multiple data warehouses.
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Experience working with large datasets and big data technologies, preferably cloud-based, such as Snowflake, Databricks, or similar. Responsibilities:The Data Engineering team is looking to fill a Senior Data Engineer responsible for designing and implementing ETL/ELT data pipelines, designing and implementing database schema/tables/views, and building batch processes leveraging Airflow for several projects.
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Guide the integration of coding and terminology standards within healthcare data systems to enhance data consistency and quality. - Extensive experience with healthcare data systems, including EMR, HIE, and population health management tools.
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Proven in-depth experience in designing, developing, and implementing Data Management, Data Governance, Data Process, Data Quality, and Data Migration/ETL solutions.
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The QA Specialist is responsible for monitoring programs for compliance toward quality standards, implementing tools used for program and service evaluation, and organizing data collection and information analysis.
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The Data Trust and Quality group is a Data Engineering team that focuses on maintaining our analytics tools and developing solutions to our data pipeline integrity and efficiency.
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Prior practical experience and implementation of Quality Engineering tools and systems such as: DOE, FMEA, SPC, RCCA, APQP, PPAP, controls plans, material control, process control, systems performance, product evaluation, MSA, metrology, automated measurement, and software is preferred.
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NPI (New product introduction) quality planning (Work Instructions and Procedure development) Interact with CPP NDT level III personnel to ensure product compliance. Experience conducting internal audits using NADCAP Audit checklist for Heat Treatment Experience operating within relevant regulatory requirements, e.g., FAA, OSHA, DCMA, ISO Systems, Quality Assurance/Control and Cost Systems ASNT or ASQ certification, Lean Manufacturing, FMEA, Process Control, SPC, CAD preferred.
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data quality jobs Title: data Company: Wells Fargo Bank in Los Angeles, CA
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