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Familiarity with data privacy standards, methodologies, and best practicesPractical hands-on experience with data technologies and Cloud Platform like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP and Azure.
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Provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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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 at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) 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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Job Title: Jr. Big Data Engineer (Urgent hiring) We are a premier IT consulting firm specializing in delivering top-tier Big Data solutions to companies across various sectors such as finance, energy, e-commerce, logistics, travel, retail, entertainment, automotive, and healthcare.
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Design and implement data-centric solutions on Google Cloud Platform (GCP) using various GCP tools like Big Query, Google Cloud Storage, Cloud SQL, Memory Store, Dataflow, Dataproc, Artifact Registry, Cloud Build, Cloud Run, Vertex AI, Pub/Sub, GCP APIs.
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Experience with big data technologies such as Hadoop, Spark, and Kafka, and cloud-based data platforms such as Amazon Redshift, Google BigQuery, or Azure Synapse Analytics. Proficiency in big data technologies, cloud computing, machine learning, and AI.
$263,408 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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5+ years working in IT with a thorough understanding of SDLC and Agile development methodology 5+ years of experience in Business Intelligence and Data Science (data mining, Machine Learning, PLS, PCA), Data architect, data engineering and Big Data 3+ years of experience as BI reporting and visualization engineer, Business Objects and Tableau Administration Proficient with one or more programming languages (SQL, Java, C.
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Experience working in GCP based Big Data deployments (Batch/Real-Time) leveraging Terraform, Big Query, Big Table, Google Cloud Storage, PubSub, Data Fusion, Dataflow, Dataproc, Cloud Build, Airflow, Cloud Composer etc.
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From sprawling public art, to a robust music scene, to nature so big and beautiful, Sanford has the small-town feel while still offering something for everyone. By applying, you consent to your information being transmitted by Jobcase to the Employer, as data controller, through the Employers data processor SonicJobs.
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6+ years of experience in data engineering working with big data systems that can process and transform data at scale. Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query). ● Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines.
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Implement Ingestion of new batch and streaming data pipelines using Scala, Databricks, and Airflow. Implementation shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across all data pipelines across the Data organization.
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big data jobs Title: data manager Company: Zendesk
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