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Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectationsNice to have:Experience in any of: machine learning, analytics, data mining, or data mart and warehouseExperience with Deep Learning platforms (Tensorflow/Keras/Spark MLlib) and SQL/Unix/ShellExperience with machine learning algorithms, NLP, and/or statistical methods a big plusYahoo is proud to be an equal opportunity workplace.
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Experience with big data tools (Cloudera, Hadoop, Spark, Map Reduce, NiFi, Sqoop, YARN) Working knowledge of distributed event streaming data platforms (Tibco, Kafka.
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Big data technologies such as Apache Hadoop, Apache Spark, or Apache Kafka. Microsoft Azure Cloud platform familiarity with Azure Data Lake Storage, Azure Databricks, Azure Data Factory, and Azure DevOps.
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Data mining/programming tools (e.g. SAS, SQL, R, Python) Implement data ingestion and processing with the help of Big Data technologies. Master Job Title :Big Data: Dev.
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Big Data Technologies: Proficient with big data technologies such as Databricks, Hadoop, Spark, and Kafka. Leverage big data technologies to efficiently process and analyze large datasets, particularly those encountered in a federal agency.
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Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka. Professional Experience: At least 5 years of experience in data engineering, with a strong focus on data integration and pipeline construction in cloud environments and enterprise data warehouses like Snowflake.
$134,500 - $215,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Optimize jobs to utilize Kafka, Hadoop, Presto, Spark, and Kubernetes resources in the most efficient way. Create different consumers for data in Kafka using Spark Streaming for near time aggregation.
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Experience with big data technologies, such as Apache Hadoop, Spark, Kafka, and others. Utilize Databricks for big data processing and streaming analytics. Stay current with emerging trends and technologies in cloud computing, big data, and data engineering.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Experience with Apache Airflow, Hive, Snowflake, Kafka, Python.
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1+ years’ experience in Big Data Distributed ecosystems (Hadoop, SPARK, Unity Catalog & Delta Lake) 1+ years’ experience in Big Data Distributed systems such as Databricks, AWS EMR, AWS Glue etc.
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Experience with Event driven Big Data streaming infrastructure and ETL/ELT frameworks (e.g., Spark Streaming, Flink, Kafka, Hive, Hadoop, Airflow, etc.) Utilize programming languages like Python, SQL, and NoSQL databases, Container Orchestration services including Terraform, Docker and Kubernetes, and a variety of Azure tools and services to build an Event Driven Big Data Streaming platform for an ELT data pipeline.
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Experience with Angular, PySpark, Hadoop, Spark, Hive, Kafka, HBase, Elasticsearch, OpenSearch, Apache, and programming languages such as Java, and Python. Exposure to other big data frame works such as MapReduce, HDFS, Hive/Hbase, Cassandra.
$125,000 - $160,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Great to haves: Experience with Databricks or S3 based data lakes Experience writing Python or Scala code Exposure to big data tools: Hadoop, Spark, Kafka, etc. As a Senior Data Engineer, you will help evolve our platform (Databricks) and our partner integrations (HubSpot, Iterable, Appcues, etc.
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Experience in developing partner led sales in collaboration with data platform and tool vendorsIn-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
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hadoop kafka big data mining jobs Company: Oath Inc
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When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
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Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
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