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Experience with any of the following: Data Architecture, Elastic Search, DBT, Airflow, Palantir Foundry, Data Quality tools, Collibra, MDM, Informatica, Spark, Snowflake, Teradata, SAP Business Warehouse, Business Objects Suite, Tableau, SAS Enterprise Miner, and other database and BI technologies, open-source Hadoop, and related technologies, data access languages such as SQL, SAS, R, Python, Scala, etc.
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Utilizing ElasticSearch and other big data technologies like MapReduce, Apache Spark and Scala. The customer's National Intelligence Community (NIC) Business Unit, USG Mission and Information Technology Division, is seeking a Database Developer that is part of an integrated team to create, update, and maintain a federated search and discovery software system to integrate data related to financial information from a variety of data providers within a cloud environment.
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Strong implementation skills and working knowledge of data structures, algorithms and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive). Experience working with big data technologies and data formats (e.g., Parquet, Delta, Iceberg.
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Knowledge of Google Search, inclusive of product capabilities and systems and of measurement capabilities, including MMM, incrementality, SQL. As one of the masterminds behind our strategic planning, forecasting and analysis, youll spend your time digging into big, complex data sets.
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Experience with analytics and data management principles such as: data acquisition and modeling, data warehousing, business intelligence, metadata management, master data management, advanced analytics and data science, “big data” techniques, public/hybrid/private cloud data management and analytics services data security, and data and analytics governance.
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In-depth understanding and experience in two or more of the following: complex e-commerce applications, massive real-time event and message processing, data lakes, Big Data transformations and analytics, IoT edge and cloud data processing, SQL and NoSQL data modeling.
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Data Analysis and Predictive Modeling: Perform statistical data analysis. Utilize data insights for capacity planning, demand forecasting, and identifying performance bottlenecks.
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Experience with any of the following: Data Architecture, Elastic Search, DBT, Airflow, Palantir Foundry, Data Quality tools, Collibra, MDM, Informatica, Spark, Snowflake, Teradata, SAP Business Warehouse, Business Objects Suite, Tableau, SAS Enterprise Miner, and other database and Bl technologies, open-source Hadoop, and related technologies, data access languages such as SQL, SAS, R, Python, Scala, etc.
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Experience with big data technologies such as Snowflake, Hadoop, Spark, Airflow, or Flink. Our engineering team at OpenSea is in search of a strong, driving, but curiousData Engineer to take charge of our data replication, ETL, and warehousing infrastructure to empower our core user experiences, trust & safety models, and business intelligence use cases.
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Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization.
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Strong expertise and working knowledge in data analysis, statistical modeling, and data visualization tools (e.g., Google Looker, BigQuery, Python, R, SQL, Tableau, etc. Lead and collaborate with internal agency teams, including account strategy, paid media, social media, public relations, search engine optimization, and UX/UI design / development teams, to identify data-driven opportunities and extract meaningful insights.
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Establish infrastructure for efficient data extraction, transformation, and loading using SQL and AWS 'big data' tools. Craft analytics tools leveraging various data sources to offer actionable insights on customer behavior (e.g., Google Analytics, Search Console, Ads) and operational efficiency (e.g., JIRA, Slack.
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Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data - HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks.
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Build data centric products that will scale well using the following platforms and technologies - Azure SQL, GCP Big Query and Graph technologies (Neo4j), big data solutions like Apache Spark, GCP Data Proc, and in Messaging platforms (Kafka)Work cross- functionally with Risk and Compliance management ecosystem to manage effective and efficient data flow and exchange.
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Tools, Collibra, MDM, Informatica, Spark, Snowflake, Teradata, SAP Business Warehouse, Business Objects Suite, Tableau, SAS Enterprise Miner, and other database and BI technologies, open-source Hadoop, and related technologies, data access languages such as SQL, SAS, R, Python, Scala.
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