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Your primary responsibilities will include laser scanning and ensuring high-quality data acquisition for projects in our expanding geographic area, this will also include scan registration and contributing to digital twin model development.
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Lead initiatives to define data governance frameworks, standards, and best practices to ensure data quality and consistency. Establish data quality metrics, monitor data integrity, and implement corrective actions as necessary.
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In this role you will be responsible for designing, developing, and maintaining data pipelines in support of data management functions such as data engineering, data integration and data quality and governance activities.
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You should provide expert-level advice to data scientists, data engineers, and operations to deliver high-quality analytics via data pipelines and APIs. At least two years two years experience designing and building highly scalable data pipelines using Airflow & Databricks.
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Expert-level professional hands-on experience in extensible data pipeline development using Databricks, Alteryx, AWS Glue and Lambda functions. Expert-level knowledge and experience in implementing software engineering security best practices and contributing to design/engineering for DevSecOps. Expert-level experience with master data management strategies, rules-based engines, and tools for multi-stage data correlation on large data sets.
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We are hiring for a Principal Product Manager (Technical) to drive the evolution of products which provide Amazon business teams and selling partners (marketplace sellers and retail vendors) with comprehensive, accurate, and standardized metrics in a timely manner to enable high quality, high velocity decisions.
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Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL. Experience with data processing frameworks and tools like Apache Spark (including Databricks), and Hadoop and knowledge of database technologies like SQL databases (e.g., MySQL, PostgreSQL.
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Proficient with Data Warehousing solutions (e.g., Redshift, Snowflake, BigQuery, Lakehouse, Data Mesh, Medallion Architecture) Cerberus Technology Solutions (CTS) is a subsidiary of CCM focused exclusively on leveraging emerging technology, data, and advanced analytics to drive transformations.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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MAX Digital is looking for a Data Operations Engineer to join our growing team and boost our data quality and data control efforts to meet customer and market demand. Develop and analyze large data sets using all required tools from data gathering, data quality check, query data, and BI.
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We're looking for a Senior Data Engineering Manager to contribute to FanDuel’s growing data and analytical needs. It also includes creating the right culture to enable a high performing data engineering teams and managing 3rd party development partners.
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Ensures operational efficiencies and customer data integrity in accordance with internal policies and procedures of SMBC and Head Office and compliance with AML/BSA/OFAC regulations. Within the Compliance Operations Department, the Account Control Group (ACG) QC is responsible for performing processes related to Know Your Customer (KYC/CIP), assessing the quality of KYC folders, assisting with specialized projects, and supporting the ACG VP with day-to-day operational processes and reporting within ACG. May act in capacity of team leader or individual contributor.
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Python, SQL, and spark expertise, along with core competencies required to ship high quality data pipelines and data tools fast. Implement data quality tests and alerting for key donation, donor, and donor engagement variables.
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New York This role is regulated by FINRA. As a Barclays Equity Research Analyst, Aerospace and Defense, you will be reviewing business and trade publications, annual reports, financial filings, and other sources to gather, synthesize and interpret data on companies followed by the business.
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Leverage orchestration tools, such as Databricks Workflows or Airflow, to orchestrate and monitor data pipelines, ensuring seamless integration, data quality, and compliance with regulatory requirements.
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data quality jobs Title: data scientist Company: Deloitte in Jersey City, NJ
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