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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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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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As an ETL/ELT Pipeline Engineer, you will be responsible for designing and building efficient data integration pipelines using GCP native tools or open-source technologies such as Python and PySpark.
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Data Migration, Integration, API’s development, Data Streaming ( Batch and continuous) and scheduling. Design and implement Data Migration and Data Integration across cloud and hybrid environments.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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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.
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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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Experience in data integration and building complex ETL pipelines using ETL tools, including Informatica, Datastage, Clover DX, AWS Glue, Knime. 5+ years of experience in building data engineering solutions utilizing AWS services (S3, Kinesis, Lambda, Glue, SNS) or Data platforms like Databricks/Cloudera.
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7+ years of hands-on experience in Data warehouse and Data Integration (ELT/ETL) Hands on experience working with Talend or SSIS as an ELT tool with Snowflake and SQL server Data Integration.
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ETL Tools: Azure Data Factory (ADF), Azure Database migration service (DMS), ETL SQL server integration services (SSIS), SQL server reporting services (SSRS), ETL extract transformation and load, Business Intelligence (BI), BCP.
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This architecture includes an Databricks, Microsoft Azure platform tools (including Data Lake, Synapse), Apache platform tools (including Hadoop, Hive, Impala, Spark, Sedona, Airflow) and data pipeline/ETL development tools (including Streamsets, Apache NiFi, Azure Data Factory.
ExpandApply NowActive JobUpdated 6 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. A Data Engineer also interfaces with other technology teams to extract, transform, and load (ETL) data from a wide variety of data sources.
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Design, develop and deliver data integration/data extraction solutions using IBM DataStage or other ETL tools and Data Warehouse platforms like Teradata, BigQuery. Tech stack: BigQuery , any ETL tool (Informatica, Talend, DataStage), Dataflow, Dataproc.
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ETL/Data integration/Streaming Talend, DataBricks, Python, Spark, Kafka. - Be an expert and drive architecture in one or more areas of data storage (Data Lakes and Warehouses), data integration, Business Intelligence and analytics.
$118,800 a yearExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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This nationwide mortgage industry leader has an immediate 9+ month contract opportunity for a Data Integration ETL Engineer/Developer with DataStage and Talend experience. 5+ Years of DataStage and Talend ETL and data integration experience.
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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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