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Verify ERP fulfillment data against customer portals, ensure data integrity and achievement daily shipment attainment. Ensure accurate inventory and work-in-progress (WIP) valuation through product auditing, cycle counts, and data verification.
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Assist in physical audits of products and verification of data in Google Sheets, NAV and Metrc. Biotrack (Seed to Sale) data entry verification and adjustments for Processing Department products.
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The Data Scientist is responsible for executing the full-scope of advanced analytic techniques with the objectives of creating quantitative and qualitative models, data mining, causal inferences, predictions, optimizations, and recommendations for Treasury team.
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Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka. As a big data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry.
$75,600 - $172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Required 10 Years Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL, Azure Synapse Required 5 Years Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL Required 10 Years Hands-on experience in Azure SQL Database, Azure SQL Datawarehouse Required 7 Years Hands-on experience in deploying and maintaining large-scale data processing pipelines.
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Experience working with large datasets and big data technologies, preferably cloud-based, such as Snowflake, Databricks, or similar. 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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Kāpili Services is charged with making the above hardcopy materials easily accessible to DTRA deterrent mission researchers in a way that provides knowledge and meaning through the use of digitization, Machine Learning (ML), Artificial Intelligence (AI), and data science.
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Reporting to the Chief Information Officer the Data Engineer is primarily responsible for developing and maintaining robust data integration pipelines between various systems such as internal OLTP databases, third-party vendor platforms, and an Enterprise Data Warehouse (EDW), scoping requirements for advanced reports, developing metrics and dashboards, and making recommendations for process improvement based on analysis of historical data.
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Demonstrated proficiency and advanced capabilities in programming and analysis using SAS/SQL/R/Python, encompassing: Data processing, extraction, and cleansing utilizing SAS, SQL, R, or Python Proficiency in SAS Macro language Application of statistical techniques to health-related clinical and economic data Generation of meaningful and easily understandable deliverables, such as descriptive data summaries, statistical tests, graphical representations, etc.
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5+ experience in Master Data Management project implementation or support, Informatica MDM trust settings, validations, IDD, e360, SIF/BES, ActiveVOS. Experience in Informatica MDM publishing, JMS, Informatica MDM Architecture and Data Flow.
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3+ years of experience with data applications and tools (Snowflake, Databricks, Spark, EMR, Presto, Datadog, DBT, etc.) We power the technology, data enablement, and convergent marketplaces required to ensure buyers and sellers can transact across all screens, across all data types, and all sales channels to ensure results for marketers.
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We are seeking a highly experienced Senior Data Engineer with a deep understanding of PySpark using Databricks or AWS Glue or AWS EMR and cloud-based databases such as Snowflake. 5+ years of experience in data engineering, with a strong background in Apache Spark and cloud-based databases such as Snowflake.
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Consolidate and review budgeting, forecast, and quarterly financial reporting (QFR) materials: Gather and analyze financial data from various business units, providing comprehensive insights to support decision-making processes.
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10+ years of experience in design and specification of: lighting systems, power systems, fire alarm systems, telcom/data systems, medium voltage power systems, UPS systems, emergency generator systems, grounding systems, and utility systems.
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data job Title: informatica Company: Edward Jones
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