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Experience in data processing roles such as database developer/administrator, ETL/Big Data developer, data analyst and/or BI analytics developer Experience with cloud platforms, big data platforms and one or more general purpose programming languages, including but not limited to: Python, SQL, Spark, Amazon Web Services Experience with DevOps principals and version control (Git preferred) End-to-end experience with data, including querying, aggregation, analysis, and visualization.
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Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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Experience in Big Data tools and technologies such as Big Query, Databricks, Snowflake, Spark, Kafka Streams. In-depth understanding of Big Data ecosystems underlying architectures to re-platform legacy systems and build integration solutions on Google Cloud platform.
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As a Staff DevOps Engineer-Hadoop Admin on our Big Data Federal Team you will help deliver 24x7 support for our Private Cloud infrastructure. Architect and drive the end-end Big Data deployment automation from vision to delivering the automation of Big Data foundational modules (Cloudera CDP), prerequisite components and Applications leveraging Ansible, Puppet, Terraform, Jenkins, Docker, Kubernetes to deliver end-end deployment automation across all ServiceNow environments.
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Our tenant is a strong cross-domain team to deliver E2E solutions covering tech areas ranging from machine learning, big data, microservices to data visualization. 3+ years of big data development experience with technical stacks like Spark, Flink, Singlestore, Kafka, Nifi and AWS big data technologies.
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Utilize Spring-Boot and Flask frameworks for creating microservices that interact with Big Data systems. Cloudera Certified Professional (CCP) or any relevant Big Data certification is preferred.
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Experience with Azure Synapse, Big Data or Snowflake is a plus. Skills required: Azure Data Factory, DataBricks, Data Lake Architecture, Azure DevOps, Python, SQL, solid understanding of Azure fundamentals and security best practices, Release management.
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake, Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). Sia Partners is looking for a talented Data Engineer to support our activities within the Data Science Business Unit. You will be working alongside with our Data Science consultants and our clients on Data Engineering topics, including creating relevant data models, developing powerful data pipelines, exposing them through various mechanisms including APIs, and using data visualization tools to efficiently present data.
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As a big data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.
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Advanced programming experience and big data experience within Python, Containerization (Docker and Kubernetes), GIT and GIT lifestyle, Databricks, Hive, Kafka, spark, PowerBI. 2+ years of experience in Big-data tools like spark, databricks.
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Building automation monitoring tools for Big Data and working with data engineering-related tools and technologies, including: Kafka, Data Warehouses, and Apache Airflow.
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Experience in Big Data tools and technologies such as Big Query, Databricks, Airflow, Spark, Kafka Streams. Experience in test automations ensuring data quality, continuous integrations build and deployment processes using Docker, GitHub, Jenkins and Unix/Linux shell scripts.
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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Experience with big data technologies such as Apache Spark. Familiarity with DevOps practices for data engineering. As a Data Engineer , you will play a key role in designing, implementing and optimizing the data infrastructure to support the organization's analytical and reporting needs.
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5+ years building scalable ETL pipelines with big data processing and/or developing applications and data sources (Apache Ni-Fi, Airflow, SSIS) Work with Data Scientists to implement strategies for cleaning and preparing data for analysis, to develop data imputation algorithms, and optimize performance of big data and machine learning systems.
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big data jobs Title: devops engineer Company: Crowdstrike
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