26 to 50 of 308 Hadoop Jobs

supervised, unsupervised, reinforcement learning), deep learning, and neural networks. Experience with data preprocessing, feature engineering, and model evaluation techniques.\Familiarity with data management and big data technologies (e.g., Spark, Hadoop, SQL, NoSQL databases). Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Strong analytical and problem-solving skills. Excellent communication and collaboration skills More ❯

clusting, dimensionality reduction, deep learning architectures). Experience with data preprocessing, feature engineering, and data visualization techniques. Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services. Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines. Strong More ❯

years of experience with a public cloud, including AWS, Micro sof t Azure, or Google Cloud 5+ years of experience with distributed data or computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka 5+ years of experience working on real-time data and streaming applications 5+ years of experience with Agile engineering practices Experience administering Databricks environments More ❯

Proficiency in Java or Scala for developing scalable backend systems and data pipelines. Solid understanding of SQL and relational databases (e.g., MySQL, PostgreSQL, Hive). Familiarity with the Apache Hadoop ecosystem (HDFS, MapReduce, YARN). Working knowledge of Apache Spark and its modules (e.g., Spark SQL, Spark Streaming, MLlib). Experience with cloud-based data platforms like AWS Glue More ❯

cloud platforms such as AWS, GCP, or Azure. Proficiency with infrastructure-as-code tools like Docker, Kubernetes, and Terraform. Advanced experience with big data technologies, such as Apache Spark, Hadoop, and Kafka. Familiarity with ML observability and orchestration tools, including MLflow, Kubeflow, and Airflow. Solid understanding of version control systems, CI/CD, and DevOps best practices. Strong collaboration More ❯

Qualifications Familiarity with the cyber domain Experience with monitoring, logging, and alerting tools (e.g., Prometheus, Grafana). Experience querying databases (SQL, Hive). Experience working with data platforms like Hadoop and Spark. Overview Noblis and our wholly owned subsidiaries, Noblis ESI , and Noblis MSD tackle the nation's toughest problems and apply advanced solutions to our clients' most critical More ❯

data architecture, integration, governance frameworks, and privacy-enhancing technologies Experience with databases (SQL & NoSQL - Oracle, PostgreSQL, MongoDB), data warehousing, and ETL/ELT tools Familiarity with big data technologies (Hadoop, Spark, Kafka), cloud platforms (AWS, Azure, GCP), and API integrations Desirable: Data certifications (TOGAF, DAMA), government/foundational data experience, cloud-native platforms knowledge, AI/ML data requirements More ❯

Preferred Skills: • Experience working in federal or regulated environments • Prior hands-on Foundry work (creating pipelines, establishing objects, monitoring asset health) • Familiarity with big data tools such as Spark, Hadoop, or Databricks • Strong communication, analytical, and troubleshooting skills Thanks and Regards Murali Sharma More ❯

and Airflow) 2+ years of experience with CI/CD tools. Strong knowledge of data storage and processing technologies, including databases and data lakes based distributed computing frameworks (e.g., Hadoop, Spark). 3+ in programming languages such as Python, Java, or Scala. Nice to have Informatica Cloud experience (IDMC) Detailed Responsibilities: Develop and Maintain Data Integration Solutions: o Design More ❯

transformation and workload management Experience with development of REST APIs, access control, and auditing Experience with DevOps pipelines Experience using the following software/tools: Big Data tools: e.g. Hadoop, Spark, Kafka, ElasticSearch Data Lakes: e.g. Delta Lake, Apache Hudi, Apache Iceberg Distributed Data Warehouse Frontends: e.g. Apache Hive, Presto Data pipeline and workflow management tools: e.g Luigi, Airflow More ❯

Provide technical leadership and contribute to all phases of the software development lifecyclefrom design to deployment. Required Skills/Experience: Hands-on experience with data engineering tools such as Hadoop, Cloudera, and Apache Spark. Proficiency with AWS services including EMR Studio. Familiarity with CI/CD pipelines, GitHub, and version control workflows. Experience working with or maintaining an Analytics More ❯

AWS data platforms and related services. Solid grasp of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies such as Spark and Hadoop, and distributed computing concepts. Proficiency in SQL and at least one programming language (e.g., Python, Java). Preferred Qualifications: Relevant certifications in data architecture, cloud platforms, or data governance. More ❯

AWS data platforms and related services. Solid grasp of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies such as Spark and Hadoop, and distributed computing concepts. Proficiency in SQL and at least one programming language (e.g., Python, Java). Preferred Qualifications: Relevant certifications in data architecture, cloud platforms, or data governance. More ❯

with Trino/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory More ❯

Python, SCALA, and/or UNIX shell scripting Expertise in machine learning techniques and statistical analysis Proficiency in SQL and NoSQL databases Experience with big data platforms such as Hadoop, Spark, and Kafka Cloud computing expertise across AWS, Azure, and other Experience in designing and implementing real-time data processing solutions Strong understanding of AI/ML applications in More ❯

years Advanced Java, R, SQL, Python coding Minimum 6+ years statistical Analysis, Machine Learning, Computer Science, Programming, Data Storytelling Minimum 6+ years big Data technologies such as Spark, AWS, Hadoop including traditional RDBMS such as Oracle and SQL Server Minimum 6+ years of data mining (preferably in a data-intensive financial company) Additional Qualifications Proficient experience in machine learning More ❯

AWS (commercial, gov cloud, secure environments). You must be proficient with Kubernetes/Microservice-based architecture (e.g., OpenShift, EKS, Docker), managed services, and large-scale processing environments (e.g. Hadoop/Spark/MapReduce) Languages and Frameworks : Expertise in common object-oriented and scripting languages, with primary skills in Java, Python, and JavaScript (React, Angular). Experience with OpenLayers More ❯

AWS (commercial, gov cloud, secure environments). You must be proficient with Kubernetes/Microservice-based architecture (e.g., OpenShift, EKS, Docker), managed services, and large-scale processing environments (e.g. Hadoop/Spark/MapReduce) Languages and Frameworks : Expertise in common object-oriented and scripting languages, with primary skills in Java, Python, and JavaScript (React, Angular). Experience with OpenLayers More ❯

automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to More ❯

automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to More ❯

automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to More ❯

automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to More ❯

automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to More ❯

work experience). Proven experience with Trino/Starburst Enterprise/Galaxy administration/CLI. Implementation experience with container orchestration solutions (Kubernetes/OpenShift). Knowledge of Big Data (Hadoop/Hive/Spark) and Cloud technologies (AWS, Azure, GCP). Understanding of distributed system architecture, high availability, scalability, and fault tolerance. Familiarity with security authentication systems such as More ❯

work experience). Proven experience with Trino/Starburst Enterprise/Galaxy administration/CLI. Implementation experience with container orchestration solutions (Kubernetes/OpenShift). Knowledge of Big Data (Hadoop/Hive/Spark) and Cloud technologies (AWS, Azure, GCP). Understanding of distributed system architecture, high availability, scalability, and fault tolerance. Familiarity with security authentication systems such as More ❯