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SQL: 1+ Years (Preferred) Data Warehousing (Snowflake, Databricks, Redshift, BigQuery, Clickhouse, etc). Craft robust ETL and ELT pipelines using tools like dbt, Fivetran, Airbyte, Matillion and/or custom Python.
RemoteExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Must have 2 plus years of experience in implementation of Data Coud using Snowflake, Azure Synapse, GCP GBQ or AWS Redshift. Must have good technical understanding and knowhow on ETL tools like Informatica, DataStage, ISIS or Talend.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Extensive experience with ETL tools, specifically Airflow, SSIS, DataStage, or Informatica. Cloud Services Management : Leverage AWS services (e.g., Amazon S3, RDS, Redshift, Lambda, Glue), and GCP to build and maintain a highly efficient data infrastructure.
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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.) Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend.
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Experience with cloud-based data offerings (Amazon AWS, Redshift, Snowflake, Google GCP, Microsoft Azure)? Snowflake, DBT, ETL Informatica, SQL, PREFERRED QUALIFICATIONS:? Experience with ETL Tools (Informatica, DataStage, Data Build Tool, etc.
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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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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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2+ years of data warehousing experience (Redshift , Snowflake , Databricks, etc.) Implementing ETL processes, moving data between systems including S3, Snowflake, Kafka, and Spark. 5+ years of experience as a data engineer building ETL/ELT data pipelines.
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Prior experience working with Snowflake/Redshift, AWS, S3. Experience in building ETL pipelines using DBT. Our category-defining enterprise platform enables organizations to operationalize trust across privacy, security, data governance, GRC, third-party risk, ethics, and compliance, and ESG.The ChallengeSenior Principal Data Engineer will be part of an innovative data team that enables Finance, Marketing, Product, Sales and to explore data and take actions that differentiate us from our competition.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Hands-on experience and expertise in Advanced SQL, Advanced Python programming, AWS Services ( such as S3, Redshift, Glue ETL, IAM, DMS, Appflow,VPC and others), SnowFlake, FiveTran, KAFKA, Airflow, Oracle Cloud and other open source tools.
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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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5+ Years of experience in ETL tools like Matillion / DataStage / Informatica / Talend5+ Years experience in using AWS Services like Kinesis Streams, Lambda, Athena, RedShift, S3, DMS, SQS, SNS, Elastic Cache and EKSStrong knowledge in Java, Python, SQL, NodeJSIdentify the opportunity for automation and design/build the end-to-end solutions.
$147,410 - $174,600 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Proficiency with one of the Cloud data-warehouses / data-lakes like Snowflake, Google BigQuery, AWS Redshift, Azure Synapse, Databricks. Deep understanding of data engineering fundamentals, ELT / ETL, latency, observability, lineage, distributed storage and distributed computing.
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Knowledge of data engineering and data warehousing concepts, including RedShift, Redshift Spectrum, AWS Glue, AWS Lambda. Experience with Databricks, Reverse ETL. Proficient in programming languages such as Python, R, SQL, and SAS.
Full-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Experience with AWS services such as Athena, Glue, DataBrew, Lambda, S3, DynamoDB NoSQL, Relational Database Service (RDS), Amazon EMR and Amazon Redshift, SageMaker, QuickSight, Kinesis, OpenSearch, Deep Learning AMIs, Lake Formation.
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