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Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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Demonstrated experience leading complex Digital and Data Transformation services sales processes with multiple team members and decision makers (C-suite level - accounting and finance executives including CFO, CIO, CTO, CDO, VP of Finance, Head of FP&A.
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Your expertise is needed on our Finance Team to collect and manage project data in compliance with Department of Treasury’s Community Development Financial Institutions Fund (CDFI Fund) program requirements, including all CDFI programs (FA, NMTC, CMF, ERP, etc.
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You Have: 3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. 3+ years orchestrating and implementing pipelines with workflow tools like Databricks Workflows, Apache Airflow, or Luigi 3+ years of experience prepping structured and unstructured data for data science models.
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Alteryx, Banking, Business, Critical Thinking, Data Acquisition, Data Analysis, Data Management, Data Operations, Data Quality, Decision Making, Financial Products, Leadership, Management Reporting, Microsoft Power BI, People Management.
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The Far Horizons program is currently doing fieldwork using two main instrument sets designed and built at the Adler: the GONet camera system, which collects all-sky nighttime environment data in the field, and the NITELite system, which is a high-altitude balloon-borne camera system that collects regional scale night-time images from the stratosphere.
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The Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling.
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Data Evangelist: Promote data product adoption through training and webinars. Best Practices: Establish and adopt best practices for analytical insights, ensuring data integrity and usability.
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Data Center / Headend Technicians TekCom Resources, Inc is currently recruiting for several Data Center / Headend Technicians for one of our national customers with needs in the Chicagoland, IL area.
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Experience building and managing production-grade data pipelines using tools such as Airflow, dbt, DataHub, MLFlow. Youll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Healthcare Analytics Practice (HAP)– Our core strength is the ability to harness and analyze large amounts of electronic healthcare data and turn it into meaningful and insightful information. QualificationsProgression towards a master’s or bachelor’s degree in economics, mathematics, data science, statistics, accounting, finance, healthcare administration or related fields.
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A Tier I technician will gain an on-the-job understanding of the mechanical, electrical, fire life safety, and security systems used in a data center environment including, but not limited to the following: electrical distribution and layout, transformers, PLC's, generators, switchgear, UPS systems, STS', ATS' PDU's, chilled water systems, CRAC/CRAH's, pre-action sprinkler systems, security hardware, CCTV, monitoring, and CMMS systems.
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DATA ARCHITECT Propose new database architecture and support data migration from an existing Legacy system to a new structure Create source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Implementation and tuning experience in the Big Data Ecosystem, (such as EMR, Hadoop, Spark, R, Presto, Hive), design principles) and Data Warehousing (such as Redshift, Teradata, Vertica, schema design, query tuning and optimization) and data migration and integration.
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Title: data Company: Dice in Chicago, Bentonville, Kansas
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