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Experience with Google Cloud Platform (GCP) using tools like BigQuery, Cloud Composer, Dataproc and Dataflow. Experience on Big Data technologies like Hadoop, Spark, any cloud platform like GCP, Azure, AWS, Snowflake.
$61,800 - $123,600 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Net Core, MVC.o Strong experience in Azure DevOps, Visual studio, SQL Server, T-SQL, SSMS, SSIS, DTSX and SSRS.o Experience with data visualization tools - SSRS, Tableau, D3, COGNOS, and Power BI.o Experience with Oracle, Teradata, Google BigQuery, Google Cloud Platform, API development is a plus.
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5+ years of experience with SQL or NoSQL database (PostgreSQL, MySQL, SQL server, Oracle, Aurora, Presto, BigQuery) Advanced level proficiency with at least one ETL / Data Orchestration technology (Azure Data Factory, SSIS, Informatica, Alteryx, Ab Initio, Pentaho, Talend, Matillion.
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As a Senior Data Engineer on the MMA National IT Data and Analytics Team, we will count on you to develop and maintain scalable data pipelines, enhance data models, and provide subject matter expertise in data acquisition and consumption pipelines on Azure, Databricks and Confluent.
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5+ years of experience implementing modern designs using at least one cloud-based solution/platform (AWS, Azure, GCP) Experience cloud-based data warehousing and data lake solutions like Snowflake, Redshift, Databricks.
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Experience with Spark and cloud databases (Snowflake, BigQuery, DeltaLake) Hands-on expertise in Big Data, Distributed Systems, and Cloud Architecture (AWS, Azure, GCP) Experience with Spark and cloud databases (Snowflake, BigQuery, DeltaLake.
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Familiarity with a Modern Data Stack (I.e., ETL tools like dbt, Airflow, Fivetran, and cloud data warehouses like BigQuery, Snowflake, Azure, or Redshift). Familiarity with a Modern Data Stack (I.e., ETL tools like dbt, Airflow, Fivetran, and cloud data warehouses like BigQuery, Snowflake, Azure, or Redshift.
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Familiarity with Hadoop, Spark, and Cloud databases (Snowflake, BigQuery, Redshift, Databricks) and stream processing frameworks (Kafka, Kinesis). Proficient in Big Data, Distributed Systems, and Cloud Architectures (AWS, Azure, GCP.
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4+ years of hands-on experience with cloud data warehousing technologies (Snowflake is preferred, BigQuery, AWS, Azure, SAP BW). Experience with SAP ERP systems – OTC, Finance, Master Data is preferred Certification in relevant areas (e.g., Snowflake, AWS Certified Data Analytics, Google Cloud Professional Data Engineer) is preferred Strong dedication to code quality, automation and operational excellence using CI/CD pipelines and unit/integration tests.
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Designing and developing large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker, Cloud IAM, etc.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming etc.
$124,372.5 - $247,200 a yearFull-timeExpandUpdated Yesterday - UpvoteDownvoteShare Job
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Certifications like Azure and AWS architects, network professional, Cisco/Palo Alto, ZScaler, etc., and Network & Security Certifications like CEH, CISSP, CCSP, CISA, CISM, etc. We are responsible for crafting the developer experience for Google Cloud Platform (GCP) developers in the Data Analytics space, including BigQuery, Bigtable, and others.
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Solid understanding of cloud services like Azure/AWS/GCP, native controls, security center, DDOS protection, cloud firewalls, CASB, express route, cloud data storage, cloud storage, Kubernetes, data sharing related technologies, NetApp, Site recovery, CDN, MS defender, MS Sentinel, AWS EC2, AWS Guard, AWS KMS, Cloud Watch, Lambda, cloud containers, etc.
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Data Warehousing: Familiarity with data warehousing concepts and technologies, like Azure Synapse, Amazon Redshift, Google BigQuery, or Snowflake. Familiarity with cloud-based data platforms (e.g., AWS Redshift, Google BigQuery, Azure SQL Data Warehouse) and related services.
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Solid understanding of DevSecOps, Git integration, Code deployment using CI/CD pipelines, managing work in an agile environment using Azure Boards, Confluence. Experience designing and building data pipelines using APIs, BigQuery and Streaming ingestion methods.
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