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Quien es ustedHaber disenado y construido previamente pipelines de datos complejos, altamente escalables/fiables, utilizando el ecosistema Big Data (Hadoop/Hive/Spark/Presto/Airflow/Kinesis o equivalentes.
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2+ years’ hands-on experience with iSeries / IBMi integration 3+ years’ experience working with Cloud technologies such as ADLS, Azure Databricks, Spark, Azure Synapse, Cosmos DB and other big data technologies.
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Fluent in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting.
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Conduct extensive collections and analytic modeling, data processing, data mining, and visualization. Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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Experience as a consulting underground hard rock mining engineer or with a technical services role in underground hard rock engineering within a mining company. WSP is currently initiating a search for a Lead Mining Engineer for our Tucson, AZ office.
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Experience with cloud and big data technologies to extract and analyze data (Snowflake, S3, Redshift, Athena, Hive, BigQuery, Spark, etc). Familiarity with housing and economic datasets a strong plus (i.e. demographic data such as Census, Claritas and economic time series data such as provided by Moody's Analytics and micro data such as IPUMS and other loan-level mortgage databases.
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In-depth knowledge of underground mining processes, including stope design, drilling, blasting, extraction, and ground support techniques. This key leadership role requires extensive experience in underground stope mining, long hole mining method, in-depth knowledge of all underground mining processes, process operations, maintenance (Underground & Surface), along with strong managerial and organizational skills.
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Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence). Our data scientists work closely everyday with project managers, subject matter experts and software engineers to work on challenges in machine intelligence, data mining, and machine learning, and work together with agility to build capabilities that impress our customers.
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Demonstrated understanding of enterprise data warehouse, big data, BI & analytics, content management and data management. Facilitate the establishment and execution of the roadmap and vision for information delivery and management; including the enterprise data warehouse, big data, BI & analytics, content management and data management.
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Experience with big data technologies such as Hadoop and Spark to efficiently process and analyze massive datasets. As Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Eagle Bank. We are a place where we take pride in our low egos, value curiosity and learning.
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Work with internal stakeholders to understand their data need and drive the design and implementation of Zooms next-gen big data enablement. Create strategic data solutions to scale both the data environment and data usage of our Big Data platform.
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Comfortable working with multi-TB cloud data warehouses (Snowflake*, Big Query, Redshift) Our current analytics toolkit consists of DOMO and dbt running on top of a Snowflake data warehouse.
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Practical experience in delivering projects in Data and Analytics, Instrumentation, Measurement, Data Collection, Big Data, Data Warehousing, Business Intelligence. Drive execution and delivery of multiple high-profile big data & analytics projects from start to finish.
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Experience with big data technologies (e.g. Apache Spark, Hadoop) and data processing frameworks. Integrate data platform infrastructure with other systems fostering seamless collaboration among teams e.g. system integration with Fivetran, Monte Carlo, Salesforce Data Cloud, Tableau, Looker, Teradata, Bigquery.
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big data mining jobs Title: workforce planning
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