TB) data sets PREFERRED QUALIFICATIONS - Master's degree in statistics, data science, or an equivalent quantitative field - Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc. - Experience programming to extract, transform and clean large (multi-TB) data sets - Experience with AWS technologies Amazon is an equal opportunities employer. We believe passionately that employing a More ❯
in the schedule. • Must be willing/able to help open/close the workspace during regular business hours as needed. Preferred Requirements • Experience with big data technologies like: Hadoop, Accumulo, Ceph, Spark, NiFi, Kafka, PostgreSQL, ElasticSearch, Hive, Drill, Impala, Trino, Presto, etc. • Experience with containers, EKS, Diode, CI/CD, and Terraform are a plus. Benefits More ❯
statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end ML pipelines. Proven ability to lead and deliver data science projects in an More ❯
that ingest millions of data points per day and develop highly available data processing and REST services to distribute data across PWM. Technologies used include: Data Technologies: Kafka, Spark, Hadoop, Presto, Alloy - a data management and governance platform Programming Languages: Java, Scala, Scripting Microservice Technologies: REST, Spring Boot, Jersey Build and CI/CD Technologies: Gradle, Jenkins, GitLab, SVN More ❯
and relational database technologies (PostgreSQL, MySQL, RDS) US citizenship and an active TS/SCI with Polygraph security clearance required Desired Experience: Experience with distributed databases and streaming tools (Hadoop, Spark, Yarn, Hive, Trino) Experience with Remote Desktop Protocol (RDP) technologies Experience with data access control, specifically Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) Familiarity More ❯
exceed their expectations Sales acumen, identifying and managing sales opportunities at client engagements An understanding of database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. Hadoop, Mahout, Pig, Hive, etc.; An understanding of statistical modelling techniques e.g. Classification and regression techniques, Neural Networks, Markov chains, etc.; An understanding of cloud technologies e.g. AWS, GCP or More ❯
exceed their expectations Sales acumen, identifying and managing sales opportunities at client engagements An understanding of database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. Hadoop, Mahout, Pig, Hive, etc.; An understanding of statistical modelling techniques e.g. Classification and regression techniques, Neural Networks, Markov chains, etc.; An understanding of cloud technologies e.g. AWS, GCP or More ❯
exceed their expectations Sales acumen, identifying and managing sales opportunities at client engagements An understanding of database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. Hadoop, Mahout, Pig, Hive, etc.; An understanding of statistical modelling techniques e.g. Classification and regression techniques, Neural Networks, Markov chains, etc.; An understanding of cloud technologies e.g. AWS, GCP or More ❯
About the Role: We are seeking a Principal Applied Machine Learning Engineer to be the foundational hire responsible for establishing Boost's machine learning capabilities. This is a high-impact, high-ownership role for someone who thrives in greenfield environments More ❯
JavaScript while utilizing the Django web framework for the backends and React for developing the client facing portion of the application Create, extract, transform, and load (ETL) pipelines using Hadoop and Apache Airflow for various production big data sources to fulfill intelligence data availability requirements Automate retrieval of data from various sources via API and direct database queries for More ❯
your way around complex joins and large datasets. Git - Version control is second nature. You know how to branch, commit, and collaborate cleanly. Bonus Skills (nice to have): ApacheHadoop, Spark/Docker, Kubernetes/Grafana, Prometheus, Graylog/Jenkins/Java, Scala/Shell scripting Team ️ Our Tech Stack We build with the tools we love (and we More ❯
your way around complex joins and large datasets. Git - Version control is second nature. You know how to branch, commit, and collaborate cleanly. Bonus Skills (nice to have): ApacheHadoop, Spark/Docker, Kubernetes/Grafana, Prometheus, Graylog/Jenkins/Java, Scala/Shell scripting Team ️ Our Tech Stack We build with the tools we love (and we More ❯
your way around complex joins and large datasets. Git - Version control is second nature. You know how to branch, commit, and collaborate cleanly. Bonus Skills (nice to have): ApacheHadoop, Spark/Docker, Kubernetes/Grafana, Prometheus, Graylog/Jenkins/Java, Scala/Shell scripting Team ️ Our Tech Stack We build with the tools we love (and we More ❯
Terraform, Jenkins, Bamboo, Concourse etc. Monitoring utilising products such as: Prometheus, Grafana, ELK, filebeat etc. Observability - SRE Big Data solutions (ecosystems) and technologies such as: Apache Spark and the Hadoop Ecosystem Edge technologies e.g. NGINX, HAProxy etc. Excellent knowledge of YAML or similar languages The following Technical Skills & Experience would be desirable for Data Devops Engineer: Jupyter Hub Awareness More ❯
of your team or organization - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience hiring, developing and promoting engineering talent - Experience communicating to senior management and customers verbally and in writing PREFERRED QUALIFICATIONS - Experience with AWS Tools and Technologies … Redshift, S3, EC2) - Experience in processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the More ❯
predictive modeling, machine-learning, clustering and classification techniques, and algorithms Fluency in a programming language (Python, C,C++, Java, SQL) Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau More ❯
years, associate's with 10 years, bachelor's with 8 years, master's with 6 years, or PhD with 4 years Deep expertise in big data platforms (e.g., Hadoop, Spark, Kafka) and multi-cloud environments (AWS, Azure, GCP) Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch) Strong programming skills in Python, Java, or Scala Familiarity with data More ❯
Washington, Washington DC, United States Hybrid / WFH Options
BLN24
Ability to manage multiple projects and priorities effectively. Preferred Skills: Experience with cloud-based data lake solutions (e.g., AWS, Azure, Google Cloud). Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of data governance and security best practices. Experience with ETL processes and tools. What BLN24 brings to the Game: BLN24 benefits are game changing. We like More ❯
Washington, Washington DC, United States Hybrid / WFH Options
BLN24
solving and analytical skills. Strong communication and collaboration abilities. Preferred Skills: Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud). Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of data governance and security best practices. Experience with ETL processes and tools. What BLN24 brings to the Game: BLN24 benefits are game changing. We like More ❯
e.g., SQL, PL/SQL, DDL, 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. - Knowledge of cloud services such as AWS or equivalent Our inclusive culture empowers Amazonians More ❯
environments (e.g. Snowflake, AWS). 6+ years of hands-on technical leadership in building large-scale, distributed data pipelines and reporting tools using big data technologies (e.g. Spark, Kafka, Hadoop), ensuring quality, scalability, and governance. Strong expertise in balancing trade-offs within complex distributed systems, focusing on data quality, performance, reliability, availability, and security. Proficient in software engineering with More ❯
US or UK Preferred Experience: Data orchestration tools (e.g. , Airflow, Prefect)Experience deploying, monitoring, and maintaining ML models in production environments (MLOps)Familiarity with big data technologies ( e.g. , Spark, Hadoop)Background in time-series analysis and forecastingExperience with data governance and security best practicesReal-time data streaming is a plus (Kafka, Beam, Flink)Experience with Kubernetes is a plusEnergy More ❯
US or UK Preferred Experience: Data orchestration tools (e.g. , Airflow, Prefect)Experience deploying, monitoring, and maintaining ML models in production environments (MLOps)Familiarity with big data technologies ( e.g. , Spark, Hadoop)Background in time-series analysis and forecastingExperience with data governance and security best practicesReal-time data streaming is a plus (Kafka, Beam, Flink)Experience with Kubernetes is a plusEnergy More ❯
/mathematical software (e.g. R, SAS, or Matlab) - Experience with statistical models e.g. multinomial logistic regression - Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive) - Experience working with data engineers and business intelligence engineers collaboratively - Demonstrated expertise in a wide range of ML techniques PREFERRED QUALIFICATIONS - Experience as a leader and More ❯
/mathematical software (e.g. R, SAS, or Matlab) - Experience with statistical models e.g. multinomial logistic regression - Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive) - Experience working with data engineers and business intelligence engineers collaboratively - Demonstrated expertise in a wide range of ML techniques PREFERRED QUALIFICATIONS - Experience as a leader and More ❯
