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Hands-on experience with big data technologies such as Kafka, Spark, HDFS, HBase, Flink, DBT, SQLMesh, etc. Build and manage data ingestion frameworks using big data technologies, ensuring high efficiency and reliability.
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Reports to: VP Data Science. The AVP will also lead and guide the data science team with modeling expertise in forecasting, optimization, data mining, analysis and analyzing complex datasets; lead and guide in the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms; and lead and guide in the production of research and analysis to quantify the impact of internal and external environments on portfolio performance.
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Familiarity with Hadoop, Spark, and other big data frameworks. - Experience with data warehousing solutions like Amazon Redshift, Snowflake and Google BigQuery. - Strong experience in database management, data migration, data modelling, ETL processes, data visualization tools and data warehousing.
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This role is ideal for a hands-on network expert proficient in data center environments , WAN technologies , and network security , capable of architecting reliable, high-performance solutions.
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Basic knowledge of Carrier based installation and acceptance testing Support Carrier technical solution pretest and migration to production activities Knowledge and hands on experience working with carrier based optical DWDM and legacy SONET technologies - 10Gb and 100Gb wavelengths, Legacy OC192 and OC48 platforms, Telco and data center structured cabling fiber optics specs.
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Experience working with Big Data technologies: Spark, Databricks or other frameworks. The candidate should possess intellectual acumen, with an engineering mindset and an interest in developing enterprise scale solutions using industry recognized cloud platforms, databases, data integration/orchestration tools, and big data technologies.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Day to Day: This person will take the base code model that has been developed by the Data Science team and will be responsible to scale it, deploy it in a more reusable way, and manage the pipeline.
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Minimum of 7 year’s of experience years of experience in Big Data/Hadoop, database and data warehouse architecture and delivery. You will have an opportunity to work in roles such as Cloud Data Engineer, Data Modeler or Data Architect covering all aspects of Data including Data Management, Data Governance and Data Migration.
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Proficiency in data analysis and the use of reporting tools such as Microsoft Power BI or similar software would be a significant plus. Detail-oriented, with a focus on data accuracy and process optimization.
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Data Visualization and Reporting: Utilize Adobe Analytics reports and dashboards to understand user flows and identify areas for improvement. Customize and manage Adobe Analytics tags, variables, and events to gather relevant user experience data.
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Experience in Identity management areas inclusive of single sign-on (SSO), multi-factor authentication (MFA), data management, identity federation, enterprise directory architecture and design, and process integration.
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Design and develop a robust data engineering infrastructure to support optimal extraction, transformation, and loading (ETL) of data from diverse sources, utilizing SQL, Microsoft Azure, AWS, and advanced big data technologies.
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6 years of experience must include: Ab initio, Informatica, Data Stage; Teradata, IBM DB2, Cognos, Oracle PL SQL; Autosys, Control-M, Erwin, XML, HTML, CSS, Unix Shell Scripts; Data Analysis, Data Processing, Code Optimization, Performance tuning; Automating Business Process and Models; Microsoft Visio, Web Services, Crystal Reports; and HP Quality Center, ALM, VSS, EME, XSD. At least 3 years must include: Hadoop, HDFS, Big Data, Hive, Spark.
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Provide hands-on support for a wide range of security technologies including, but not limited to SIEM, IDS/IPS, HIDS, malware analysis and protection, content filtering, logical access controls, identity and access management, data loss prevention, firewalls, and content filtering technologies.
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Knowledge of industrial firewall concepts and functions (e.g., Single point of authentication/audit/policy enforcement, message scanning for malicious content, data anonymization for PCI and PII compliance, data loss protection scanning, accelerated cryptographic operations, SSL security, REST/JSON processing.
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big data jobs Company: Citi in Irving, Schuyler, Nebraska
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