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Developing and maintaining complex ETL mappings, workflows, and UNIX shell scripts in a Data Warehouse environment, based on technical specifications and other supporting documentation, using Informatica PowerCenter, Unix Shell Scripts, advanced SQL, and Autosys/Tidal Enterprise Scheduler, used for data integration.
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Must have extensive experience in ETL development, Data Ingestion and Data Integration using API/microservices based approach. Experience in integration technologies like Boomi, Pega, MuleSoft, API / Microservices based integration.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend. Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.
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Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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Familiarity/experience with data integration and data pipeline tools (e.g., Informatica, Synapse, Apache NiFi, Apache Airflow) Strong knowledge of Extraction, Transformation and Loading (ETL) processes using frameworks like Azure Data Factory, Synapse, Databricks, Informatica by gathering requirements from the stake holders or analyzing the existing code and perform enhancements or new development.
ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Hands-on experience working with Azures PaaS offerings such as Purview, Databricks, Azure Data Lake Storage, Data Factory as well as monitoring of the environments. Implement data engineering, ingestion, and curation functions on Azure cloud using Azure native programming.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Experience with data integration tools (e.g., Informatica, Talend, Alteryx, SSIS etc) to carry out an ETL (Extract, Transform & Load) to move data from disparate systems to Master Data Management Hub.
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As a Senior Data Platform Engineer on the MMA IT Data and Analytics Team, we will count on you to design, monitor, build, and automate data pipelines. Learn more about what makes us different and how you can thrive as a Senior Data Platform Engineer at MMA.Marsh McLennan Agency (MMA) provides business insurance, employee health & benefits, retirement, and private client insurance solutions to organizations and individuals seeking limitless possibilities.
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A minimum of eight years' experience in providing complex consultative services in the following focus areas: information strategy, data architecture, information/data governance, master data management, data quality, data integration.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Experience: 5 years of technical experience performing ETL development; developing and scheduling batch jobs; developing UNIX Shell Scripts for data validation and reconciliation; designing relational and dimensional databases; performing data integration in AWS using Python and HIVE; developing Python data integration and validation scripts; and performing real-time data integration using messaging queue(MQ.
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Experience with Master Data Management platforms and tools such as Informatica MDM, C360, Reltio, Profisee, Semarchy. A minimum of two years’ experience in providing complex consultative services in the following focus areas: information strategy, data architecture, information/data governance, master data management, data quality, data integration.
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A minimum of five years' experience in providing complex consultative services in the following focus areas: information strategy, data architecture, information/data governance, master data management, data quality, data integration.
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Good to have past experience on few other integration platforms such as Dell Boomi, SnapLogic, TIBCO, WebMethods, Informatica, Oracle, and IBM.Knowledge of cloud integration (iPaaS), service enablement (API), the data integration disciplines of messaging (ESB) for real-time data propagation, service-oriented architecture (SOA) for information sharing, and extract, transfer and load (ETL) for data staging and movement.
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Knowledge of data integration methods and techniques such as use of APIs to distribute data from MDM to subscriber systems. The Data Governance and Data Quality Analyst will specialize in serving EY clients in the areas of Data Strategy, Data Governance, Data Quality, Data Definition and Usage, and Data Management.
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Assisting in the strategy and implementation of Master Data Management, Data Governance, Enterprise Data Management, Enterprise Content Management and Knowledge Management. We’ll look to you to provide our clients with a unique business perspective on how Data Strategy, Data Governance, Data Quality, Data Definition and Usage, and Data Management can transform and improve their entire organization – starting with key business issues they face.
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