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Hands-on production experience with orchestration systems such as Airflow. Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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The ideal candidate has extensive, hands-on experience with Snowflake or similar cloud-based data warehousing solutions. RequirementsBachelor’s degree in Computer Science, Information Technology, Data Science, or a related field5+ years of experience in data analysis, data engineering, or a related fieldProficiency with data analysis tools and languages such as SQL, Python, R, etc.
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Expert-level professional hands-on experience in extensible data pipeline development using Databricks, Alteryx, AWS Glue and Lambda functions. Expert-level professional hands-on experience with RDBMS, ETL scripting tools and IDEs, data pipeline development, and management using orchestration/monitoring tools.
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Expert-level knowledge and experience in implementing software engineering security best practices and contributing to design/engineering for SecOps. Expert-level experience with master data management strategies, rules-based engines, and tools for multi-stage data correlation on large data sets.
$248,600 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Your journey will start with onboarding and enablement, further refining your business skills through a combination of hands-on experience in customer engagements and training. You will report to a Value Engineering Orbit Program Manager based in the NYC or Raleigh office.
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You want to work in a fast, high-growth startup environment that respects its engineers and customersYou can design simple and performant architecture to solve problems at high scaleBonus Point: You have hands-on engineering experience with at least one of the major cloud providers – AWS, Azure, GCPDatadog values people from all walks of life.
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Extensive hands-on experience with AWS ecosystem data services, including tools like DBT, Airbyte, Airflow, and AWS Glue, for data modeling, pipeline development, performance optimization, and ensuring data provenance.
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Hands-on expertise in ETL/Data pipeline and data lake platforms like Spark/Hadoop/Databricks/EMR. Strong knowledge of cloud platforms such as AWS, Azure, or Google Cloud, with hands-on experience in migrating on-premises data warehouses to the cloud.
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Hands-on experience with data warehousing solutions, for E.g. Snowflake or similar platforms. This role requires a hands-on approach to managing the end-to-end data lifecycle, Analyze complex and large datasets to provide insights that drive business decisions and optimize processes.
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2+ years of data engineering experience developing large data pipelines. As a member of the Data Capture team you will establish the foundational set of core platform frameworks and pipelines which are a vital key to success – enabling dozens of engineering and analytical teams to unlock the power of data to drive key business decisions and provide engineering, analytics, and operational teams the critical information necessary to scale the largest streaming service.
$199,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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This is a hands on Data Engineering & Developer role, with experience in development and implementation of Data Lake, Azure Data Factory, and Databricks. Hands-on experience with SAP from Data Engineering/BI Development, Azure services, including Azure Data Factory, and Databricks.
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Hands-on in Databricks SQL, PySpark Expertise in data modeling, data mappings, understanding the data model changes, and proposing the best practices and guidelines.
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Advanced knowledge of the Hadoop ecosystem and Big Data technologies Hands-on experience with the Hadoop eco-system (HDFS, MapReduce, Hive, Pig, Impala, Spark, Kafka, Kudu, Solr) The Data Engineer is responsible for building Data Engineering Solutions using next generation data techniques.
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Hands on development experience with: Python, Spark, SQL, Cloud-based ETL tools, Azure Data Factory/Databricks and Snowflake. 3+ Years of experience providing data solutions, architecture, design and delivery, in a Data Engineering role within a large financial institution.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Experience in re-engineering and migrating on-premises data solutions to and for the cloud. We are looking for someone who is passionate about data, analytics and cloud engineering to join us as we modernize our legacy environments and migrate to modern cloud data platforms (AWS, Spark and Snowflake.
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hands on data engineering jobs Title: data engineer in New York, Amarillo, Texas
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