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Modern Data Stack experience (Snowflake, Synpase, Databricks, Redshift, DBT, and/or Airflow) 10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science.
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You will be part of Modern Engineering team responsible for designing, building and maintaining standardize DevSecOps pipeline template and deployment platform. We are currently seeking a summer intern for our Modern Engineering department.
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You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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Minimum 2 years of management and leadership experience Knowledge of Windows workstation platforms, Azure AD, Intune/Modern Management, GPO, Microsoft o365, Microsoft Endpoint Configuration Manager (formerly SCCM) Limited immigration sponsorship may be available Preferred Technical skills: Data Science / Analytics using a multitude of data sources.
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Experience with AWS cloud services : EC2 , EMR, RDS, Redshift , Modern data platforms, Snowflake , dbt , Fivetran and Airflow. 5+ years in data engineering with detailed knowledge of data warehouse technical architectures , infrastructure components , ETL ELT.
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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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Familiarity with modern ETL integration solutions (SSIS, Ab Initio, Datastage, Informatica, Azure Data Factory). The Data Architect will be held accountable for the following responsibilities: Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platformsCreate standards, design patterns, and best practices for ETL development in an enterprise data warehouse environment.
$115,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Good understanding of data engineering fundamentals, ELT / ETL, latency, observability, lineage, distributed storage and distributed computing. The Data Engineering team at System1 is focused on building data assets, catalog, frameworks, and automation to ensure smooth running data pipelines and infrastructure.
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Strong Technical Background: Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL. Experience with data processing frameworks and tools like Apache Spark (including Databricks), and Hadoop and knowledge of database technologies like SQL databases (e.g., MySQL, PostgreSQL.
$210,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Requirements: 8 years of professional experience in Data engineering, data product development and software product launches Real-Time data streaming platforms like Apache Kafka, GCP Pub/Sub o Microservices architecture to deliver large-scale real-time data processing application.
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Minimum 3 years' experience working with Cloud technologies such as Synapse pipelines, Azure Data Factory (ADF), ADLS, Azure Databricks, Spark, Azure Synapse, and other modern data ETL/ELT technologies.
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Minimum 5 years' experience in data engineering with a proven track record in the Azure ecosystem and with Azure DevOps. Minimum 5 years' experience engineering and operationalizing data pipelines with large and complex datasets.
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Designs, develops, and implements ETL/ELT processes using Azure Data Factory, Synapse pipelines, Databricks Notebooks, Event Hub to build integrations from Saas sources such as Service Now, Workday, Dynamics CRM, and Eloqua.
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As a technical manager, you set the boundaries and expectations for delivering a quality product and timely solutions; you are an avid promoter of process improvement; you seek out and promote best practices; you own and refine the technical architecture, continually investing in refactoring and refinement to incorporate modern engineering tools and practices.
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A strong understanding of modern cloud technologies and a history of building and managing scalable data engineering teams is essential. Integrate these pipelines with other data engineering tools such as dbt, AirFlow, Iceberg, DuckDb, RedShift, Tabular.io. PowerBI, Tableau, Open Metadata, and knowledge of Graph DB will be a plus.
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modern data engineering jobs Company: Chenega Corporation
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