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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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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. 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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Deliver state-of-the-art Monitoring, Analytics and Actionable Business Insights by employing new tools, Big Data systems, Enterprise Data Lake, AI, and Machine Learning methodologies that improve efficiencies across a variety of functions in the company: Cloud Operations, Customer Support, Product Usage Analytics, Product Upsell Opportunities enabling to have a significant impact both on the top-line and bottom-line growth.
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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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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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Build components of large-scale data platform for real-time and batch processing, and own features of big data applications to fit evolving business needs. 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.
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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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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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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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Experience with big data technologies such as Apache Spark. Collaborate with stakeholders to understand business requirements and design Snowflake solutions that support effective data analysis and reporting.
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A strong foundation in statistics, mathematics, computer science, or a related field, with technical expertise in data analytics, big data analytics, automation, and data visualization tools.
$156,000 - $312,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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 in Big Data tools and technologies such as Big Query, Databricks, Airflow, Spark, Kafka Streams. Experience in a data science or engineering role applying Client to solve business problems.
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big data jobs Title: business analyst Company: Verizon
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