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A Data Engineer also interfaces with other technology teams to extract, transform, and load (ETL) data from a wide variety of data sources. Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend.
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As a member of the Data Engineering Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain. Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, Application Architecture like microservices, API, and realtime streaming, ETL and Data Engineering technologies like PySpark, Glue, Snowflake, and a variety of AWS tools and services.
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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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1-5 for mid) 3 to 5 years of ETL development experience with any leading platforms (Informatica/SnapLogic/Dell Boomi/Talend/Sterling Integrator) 1-5 for mid) 3 to 5 years of ETL development experience with any leading platforms (Informatica/SnapLogic/Dell Boomi/Talend/Sterling Integrator.
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ETL tools Teradata, MS SQL Server, Data Transformation Services (DTS) Export/Import, SQL Server Integration Service (SSIS), ADF, DataStage, Azure Synapse. ETL tools Teradata, MS SQL Server, Data Transformation Services (DTS) Export/Import, SQL Server Integration Service (SSIS), ADF, DataStage, Azure Synapse.
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The ETL engineer will support a cloud-based analytics platform based on AWS using Informatica Power center and Snowflake. 10 years of ETL experience in Informatica tools or similar technology.
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In depth understanding of Enterprise Data Hub Architecture, mirror, transformation & reporting layer concepts and ETL within Azure framework. Title: Lead Azure Data Engineer (Production Support.
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1+ year with ETL, PySpark, SnowFlake, and data engineering. Develop application functionalities that have direct impact to the application user experience, while working on the data pipeline ETL to strengthen data analytics for improvement identification.
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Experience with ETL tools such as SSIS, Informatica, Astronomer, DBT, or DataStage. Develop and maintain ETL processes to integrate data from various sources into the data warehouse. Experience with ETL tools such as SSIS, Informatica, Astronomer, DBT, or DataStage.
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Design Data Lake and load the data to Data Lake using ETL and PYSPARK-Work with AWS- EC2, VPC, EBS, Athena, Aurora, RDS, DMS, EMR, S3, Redshift. Migrate SPOTFIRE reports to Power BI. Have experience with Power BI. TECHNICAL SKILLS -ETL Stack: Informatica CAI, B2B Data Exchange, IDQ/BDQ, Power Center, MDM, BDM/DEI, SAP BODS, MS- SSIS, AWS Glue, AWS DataBrew.
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Quality Assurance Engineer Consultant (Must-Have Skillset: ETL Testing, Data Driven Testing, Enterprise Data Warehouse Testing) Must be experienced in Data Warehousing Projects with good knowledge of ETL testing.
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Ability to use ETL tools (such as Alteryx) and visualization tools (Microsoft Power BI). Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next. You will be working with, and learning from, highly talented colleagues on challenging and complex assignments.
$109,400 - $200,500 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Experience in architecting data pipelines and solutions for both streaming and batch integrations using tools/frameworks like Glue ETL, Lambda, Google Cloud DataFlow, Azure Data Factory, Spark, Spark Streaming, etc.
$99,000 - $148,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge. Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark SQL & Spark Streaming.
ExpandApply NowActive JobUpdated 11 days ago
etl job Title: machine learning engineer Company: Advantis Global in New York, NY
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