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Including Bloomberg, JPMorgan Chase, and eBay. To be successful in this role, you should have hands-on development experience in Salesforce and the ability to work directly with stakeholders to translate business requirements into technical requirements.
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2+ years of hands-on experience with data engineering, using tools like Python, SQL, DBT (Data Build Tool), ascend.io, or Informatica with source code control in Gitlab/Bitbucket.
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The Lead Data Scientist at The Friedkin Group (TFG) will spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives.
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Hands-on experience implementing enterprise metadata management programs, including deployment of enterprise taxonomy and ontology, and delivering data governance solutions. - Minimum of 4 years of hands-on experience implementing ASG Rochade data catalog, data governance, data lineage, data privacy, and data quality capabilities.
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Reporting to the Chief Data & Analytics Officer, this Sr Director, Head of Data Engineering is a hands-on engineering leader to lead execution of enterprise data strategy, implement operating model, and evangelize analytics innovation.
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Experienced in cloud architecture, design, and hands on knowledge of core CRM application, data integration & mastery services such as SalesForce, MuleSoft, Informatica. Ability to lead large scale data projects in a cloud or cloud/ on premise hybrid model.
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Hands-on experience with rapid prototyping techniques including 3D printing, laser cutting, PCB routing, CNC, etc. Practical experience with automation, scripting, and programming with an emphasis on data analysis, and/or controlling test equipment.
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Our growing data teams are looking for a savvy Lead Data Engineer to join and help build and evolve the next generation of Audience & Identity data platform that handles data at scale and uses state-of-the-art technologies to unlock the data's business value.
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This position may be filled by either a Data Center Engineer level or a Principal Data Center Engineer level based on the qualifications listed. Basic Qualifications: Data Center Engineer (T02): Bachelor of Science Degree in a STEM (Science, Technology, Engineering or Math) related field with 2 or more years of engineering experience or MS with 0 years or more year of engineering experience or Ph. D. with 0 or more years of engineering experience Active in scope DoD Top Secret Clearance Ability to obtain and maintain initial Special Program Access (SAP/PAR.
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3+ years of hands-on experience with AWS services like S3, EMR, Glue, EC2, ECS, IAM, Cloudformation, Athena, Lambda, and other AWS services. 5+ years of hands-on work in the field of software development.
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5-7 years of hands-on experience with Hadoop, Hive, Apache Spark, Scala. Hands on working experience in any messaging platform like Kafka is preferred. Hands on knowledge in NoSQL like Cosmos DB along with RDBMS like MySQL, Postgres is plus.
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Hands on experience installing, configuring, upgrading AD configuration changes, schema extensions/modifications, set up of GPO's, OU's, trusts, metc. Advanced hands on experience with PowerShell scripting and use of Splunk.
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Assist with internal communications and employee engagement strategy for JPMorgan Chase Commercial Banking's Community Impact and Commercial Real Estate divisions, including town halls and employee events, executive messages, internal newsletters, recognition opportunities, talking points and editorial stories; write, edit and maintain quality control of compelling stories and content.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
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Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance. Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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hands on lead engineer data jpmorgan chase jobs Company: Stryker in Morgan-city, Louisiana
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