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Access to multiple cloud-based and on-prem data environments (e.g., Snowflake, Teradata, and Google Cloud Platform) 1+ years of experience utilizing SQL and/or Python, R, Hadoop. Access to multiple cloud-based and on-prem data environments (e.g., Snowflake, Teradata, and Google Cloud Platform.
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The candidate will connect to existing SQL Server, Oracle, Teradata, and Hadoop databases to query reporting data for key business stakeholders. Responsibilities:The Analytics and Model Development team relies on a variety of systems / platforms including, but not limited to, Excel, SQL, Tableau, Alteryx, PowerBI, and SAS. The candidate will work across both Analytics and Data Management spectrums to source resource planning and call performance data / metrics and compile into Executive level dashboards on a project or ad hoc basis.
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Ability to work with extremely large data sources from multiple platforms such as SQL Server, Oracle, Teradata, Hadoop, and the mainframe. Experience with Hadoop, Python or other Big Data tools desired.
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Job Title: Lead Hadoop Application Support Engineer. Teradata/Oracle 6 + Years (nice to have) Note: Must have industry experience to Understand software development In the Hadoop space.
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5+ years of experience with fraud or credit risk analytics in financial institutions. Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary. 8+ years of experience with SAS (SAS Enterprise Guide/Studio) and SQL.
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X UNIX Shell scripting, Autosys, Cloudera CDP, Hadoop (Hive, Impala, PySpark, Scala) and Data analysis. Our client, a fortune 50 financial services firm is seeking a Teradata Engineer. Job Title: Teradata Engineer.
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Experience working with Big Data environments (i.e., Hadoop, Teradata) Experience with analytical tools such as Python, R,Tableau, and. Proficiency with SQL, Alteryx, Adobe/Web Analytics/Web.
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Skills Required: Requires experience in the following: ThoughtSpot; Tableau; Qlik Sense; Microsoft Excel; Alteryx or related reporting tools; SQL Server; Oracle EPBCS; InformEnt; MS Access; Teradata SQL Assistant; Snowflake; Hadoop or related data warehouse tools; JIRA; Agile Methodology; Logical Data Modeling; and Microsoft Visio.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Minimum education and experience required: Master's degree in Information and Technology Management, Information Technology or related field of study plus 3 years of experience in the job offered or as Business Intelligence Analyst, Cognos Report Developer, or related occupation.
ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Big Data Architecture, Cloud Data Platforms Architecture (Azure, Databricks, Snowflake), In-house Big Data Platforms (Hadoop, Teradata, Exadata) Big Data Architecture, Cloud Data Platforms Architecture (Azure, Databricks, Snowflake), In-house Big Data Platforms (Hadoop, Teradata, Exadata.
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Handle complex migrations from legacy Teradata warehousing solutions or on-prem Hadoop/Hive to Big Query in GCP. Cloudera Hadoop/Hive Rally Agile Framework. Job Title: BigData Developer with Hadoop / Hive.
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Databases – Oracle / DB2 / MySQL / Postgres / Teradata / MongoDB / Cassandra / Snowflake. Hadoop Distributions – Cloudera / Hortonworks / MAPR / Databricks. Experience in working on AWS ecosystem as a whole and should have experience in migrating ETL pipelines from Talend / Informatica/Abinitio to Hadoop / Glue / Spark.
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3+ years of database systems like Hadoop, Teradata, Redshift, Oracle, MySQL, PostgreSQL, MongoDB, Neo4j, Cassandra. 3+ years of database systems like Hadoop, Teradata, Redshift, Oracle, MySQL, PostgreSQL, MongoDB, Neo4j, Cassandra.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Using relational databases like Teradata, Oracle, SQL Server and pulling data from Hadoop/HIVE SQL/EDW data warehouses. Data visualization skills and hands-on experience using Tableau and/or Qlik with SQL skills.
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Strong data analysis skills Hands-on experience in integration development, testing, and deployment experience Exposure to disparate databases like Teradata, Hadoop, SQL server, data lakes, Data virtualization concepts, SQL query optimization, performance tuning, materialized views and advanced ANSI SQL Solid understanding of end-to-end data life cycle and good to have exposure to container platforms like OpenShift and Kubernetes.
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