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Artificial Intelligence (AI), Big Data, Cloud Computing, Computer Coding, Critical Thinking, Machine Learning, Microsoft Power BI, Model Building, Problem Solving, Python (Programming Language), Statistical Analysis.
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Work with AWS big data technologies including EMR, Glue, S3, EKS, Lambda, Athena, RDS. 6+ years’ experience working within the AWS Big Data/Hadoop Ecosystem (EMR, Glue and Athena.
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2+ years working Extensive experience in Big Data Engineering 1+ years working experience in Python-based data integration and pipeline development. Mentor and guide junior data engineers in the team Drive and implement automation to empower the organization to scale efficiently and with flexibility Keep up to date with new technologies and methodologies related to data engineering and apply them to improve the data platform Requirements: Bachelor or equivalent 1+ years working Experience in AWS Redshift, Databricks, BigQuery, Oracle, or Graph databases.
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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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Databricks Implementation: Utilize Databricks for advanced data processing, machine learning, and big data analytics, integrating with Snowflake for seamless data access and analysis.
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GCP Data Engineer (Standard) with skills Big Data, Kafka, Python, Scala, Apache Spark for location Poland. Sub Skill(s): Big Data. Primary Skill: Data Engineering.
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Specialized training in Data Engineering, Data Science, Machine Learning, Big Data Platforms (Spark, Kafka, Hadoop, H2O, etc.) LICENSING/CERTIFICATION Any certification specializing in data engineering, big data, data science, machine learning, artificial intelligence, or statistical analysis from accredited institutions of higher learning.
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Hands-on experience with Databricks for big data processing and analytics. Minimum of 10 years of experience in data engineering roles and 2+ years leading / maintaining data DevOps for Data Pipeline and ETL solutions with a focus on SQL, Databricks, Postgres, and Redshift.
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The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.
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Expert knowledge of Big Data and AWS concepts (Lambda, S3, EC2, EMR, Spark) Foursquare's flexible building blocks include technology to maximize marketing impact and drive incremental real-world engagement (Attribution, Audience, Proximity, SDK); data to deeply understand points of interest and real-world behavior patterns (Places and Visits), and tools to conduct advanced analysis, data enrichment, unification and visualization (Studio.
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Build high-performing data processing frameworks leveraging Google Cloud Platform and utilizing GCP Services like Big Query, Python, Composer, Dataflow, GKE, Pub-Sub, Cloud Monitoring. As a member of the Data and Analytics organization, you will be responsible for designing, building, and maintaining best-in-class data engineering pipelines aimed at driving best-in-class solutions primarily using Cloud platforms like GCP. You will collaborate with cross-functional teams, including data scientists, analysts, business SME's and software engineers, to ensure the efficient and reliable processing, storage, and retrieval of data.
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Implement solutions using big data technologies such as Hadoop, Spark, and others to handle large-scale datasets. Experience with big data technologies and data warehousing.
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Domain expertise: programming languages, data analytics, machine learning (ML/AI), DevSecOps, Cloud, Big Data. Demonstrate expert-level knowledge/experience in Big data and Cloud technologies: Spark ML, Splunk, Elastic Search, Apache NiFi, AWS Glue, Cribl.io Logstream, and Hadoop.
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Experience with UI/UX development & design systems: CSS, Web Components, Less, Sass Experience or exposure in big data and event streaming technologies: Spark, Kafka, etc. Experience or exposure in build and CICD technologies: GitHub, BitBucket, Azure DevOps, Maven, Jenkins, Nexus or Sonar Exposure to Agile development concepts Exposure quality assurance technologies: ATDD, Selenium, Cucumber, JUnit, NUnit, SoapUI or Postman Exposure of data management methodologies Exposure to serverless architectures and computing concepts Compensation Starting base salary: $92,114 - $156,880 per year.
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Job Title: Sr. Big Data Developer. Job Description : 8+ years of extensive IT experience with multinational clients working in diverse fields of software development lifecycle with experience in Big Data/Hadoop Ecosystem.
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big data jobs Title: data administrator Company: Kforce Inc
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