1 to 25 of 172 Apache Hive Jobs

/metadata structures, data flows, and models Experience creating visualizations with Tableau or comparable programs Demonstrated experience writing and modifying SQL Demonstrated experience with Apache Hive, Apache Spark, and HDFS or S3 Demonstrated expertise developing software using Neo4j, Python, or Java Knowledge of development tools such as More ❯

with NoSQL data persistence - DynamoDB, MongoDB, etc. DevOps mindset - knowing how to automate development and operational tasks Big data or data science background: ML, Apache Spark, Apache Hive, machine learning #J-18808-Ljbffr More ❯

Working experience in Palantir Foundry platform is must • Experience designing and implementing data analytics solutions on enterprise data platforms and distributed computing (Spark/Hive/Hadoop preferred). • Proven track record of understanding and transforming customer requirements into a best-fit design and architecture. • Demonstrated experience in end More ❯

with big data technologies such as Hadoop, Spark, or Hive. Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow. Proficiency in Python and at least one other programming language such as Java, or Scala. Willingness to mentor more junior members of the More ❯

MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results More ❯

Lambda usw. Umfangreiches Verständnis von Datenbankkonzepten und -technologien, einschließlich relationaler Datenbanken und NoSQL-Datenbanken. Praktische Erfahrung mit ETL-/ELT-Tools und -Frameworks wie Apache Spark, Apache Airflow, AWS Glue und/oder AWS Data Pipeline. Kenntnisse in der Datenmodellierung und -optimierung für analytische und Machine-Learning-Anwendungen. … Erfahrung mit der Programmierung in Sprachen wie Python, Scala und/oder ähnlichen Sprachen. Vertrautheit mit gängigen Big-Data-Technologien und -Konzepten wie Hadoop, Hive, MapReduce, Apache Kafka, sowie Streaming-Technologien wie Kinesis, Apache Flink und/oder ähnlichem. Kenntnisse in der Implementierung und Verwaltung von Datenpipelines More ❯

to streamline data workflows and reduce manual interventions. Must have: AWS, ETL, EMR, GLUE, Spark/Scala, Java, Python. Good to have: Cloudera – Spark, Hive, Impala, HDFS, Informatica PowerCenter, Informatica DQ/DG, Snowflake Erwin. Qualifications: Bachelor's or Master's degree in Computer Science, Data Engineering, or a More ❯

and migration of these data warehouses to modern cloud data platforms. Deep understanding and hands-on experience with big data technologies like Hadoop, HDFS, Hive, Spark and cloud data platform services. Proven track record of designing and implementing large-scale data architectures in complex environments. CICD/DevOps experience More ❯

and migration of these data warehouses to modern cloud data platforms. Deep understanding and hands-on experience with big data technologies like Hadoop, HDFS, Hive, Spark and cloud data platform services. Proven track record of designing and implementing large-scale data architectures in complex environments. CICD/DevOps experience More ❯

platforms. Experience in writing efficient SQL queries and implementing complex ETL transformations on big data platforms. Experience with Big Data technologies like Spark, Impala, Hive, Redshift, Kafka, etc. Experience in data quality testing; capable of writing test cases and scripts, and resolving data issues. Experience with Databricks, Snowflake, Iceberg More ❯

given constraints • Excellent diplomacy and communication skills with both clients and technical staff • Desired Skills • Proficiency in Python and Scala • Experience using Spark and Hive • Experience with Qlik or other data visualization administration • Experience completing Databricks development and/or administrative tasks • Familiarity with some of these tools: DB2 More ❯

Experience with AWS ecosystem or other big data technologies such as EC2, S3, Redshift, Batch, AppFlow AWS: EC2, S3, Lambda, DynamoDB, Cassandra, SQL, Hadoop, Hive, HDFS, Spark, other big data technologies Understand, Analyze, design, develop, as well as implement RESTful services and APIs About Us: SPECTRAFORCE is one of More ❯

analytics, or data science, with the ability to work effectively with various data types and sources. Experience using big data technologies (e.g. Hadoop, Spark, Hive) and database management systems (e.g. SQL and NoSQL). Graph Database Expertise : Deep understanding of graph database concepts, data modeling, and query languages (e.g. More ❯

Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL: Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data … Factory, Talend, and Apache Airflow. AI & Machine Learning: Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, and MXNet. AI Services: AWS SageMaker, Azure Machine Learning, Google AI Platform. DevOps & Infrastructure as Code: Containerization: Docker and Kubernetes. Infrastructure Automation: Terraform, Ansible, and AWS CloudFormation. API & Microservices: API Development: RESTful API design and More ❯

preferably in Financial Services) in building enterprise Cloud applications based on high-volume data processing frameworks, ETL development using distributed computing frameworks such as Apache Spark, Hadoop, Hive. Experience with optimizing database performance, scalability, and ensuring data security and compliance. Experience with event-based, micro-batch, and batched high More ❯

pipelines Proficiency in SQL Experience with scripting languages like Python or KornShell Unix experience Troubleshooting data and infrastructure issues Preferred Qualifications Experience with Hadoop, Hive, Spark, EMR Experience with ETL tools like Informatica, ODI, SSIS, BODI, DataStage Knowledge of distributed storage and computing systems Experience with reporting and analytics More ❯

TensorFlow, XGBoost, PyTorch). Strong foundation in statistics, probability, and hypothesis testing. Experience with cloud platforms (AWS, GCP, Azure) and big data tools (Spark, Hive, Databricks, etc.) is a plus. Excellent communication and storytelling skills with the ability to explain complex concepts to non-technical stakeholders. Proven track record More ❯

with team members, stakeholders and end users conveying technical concepts in a comprehensible manner Skills across the following data competencies: SQL (AWS Athena/Hive/Snowflake) Hadoop/EMR/Spark/Scala Data structures (tables, views, stored procedures) Data Modelling - star/snowflake Schemas, efficient storage, normalisation More ❯

platforms implementation Hands-on development and architecture experience in Java or Scala, Microservices Hands-on development and architecture experience in big-data ecosystem – Hadoop, Hive, Impala, NOSQL Hands-on development, architecture and leadership experience in distributed computing technologies – Spark, Flink Hands-on development, and architecture experience in caching, In More ❯

lake platform and different components in the data lake such as Hadoop, Amazon S3 etc. Work on SQL technologies on Hadoop such as Spark, Hive, Impala etc Help continually improve ongoing analysis processes, optimizing or simplifying self-service support for customers Must possess strong verbal and written communication skills More ❯

a week. Flexibility is essential to adapt to schedule changes if needed. Preferred Requirements Experience with big data technologies like: Hadoop, Spark, PostgreSQL, ElasticSearch, Hive, Drill, Impala, Trino, Presto, etc. Experience with containers EKS, Diode, CI/CD, and Terraform are a plus Work could possibly require some on More ❯

FireHose, Lambda, and IAM roles and permissions - Experience building large-scale, high-throughput, 24x7 data systems - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience providing technical leadership and mentoring other engineers for best practices on data engineering Our inclusive culture empowers Amazonians to deliver the More ❯

MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results More ❯

SparkSQL, Scala). Experience with one or more scripting language (e.g., Python, KornShell). PREFERRED QUALIFICATIONS Experience with big data technologies such as: Hadoop, Hive, Spark, EMR. Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results More ❯

the big 3 cloud ML stacks (AWS, Azure, GCP). Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi. Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka. Experience with workflow orchestration … tools like Apache Airflow. Experience with containerisation using Docker and deployment on Kubernetes. Experience with NoSQL and graph databases. Unix server administration and shell scripting experience. Experience in building scalable data pipelines for highly unstructured data. Experience in building DWH and data lakes architectures. Experience in working in cross More ❯