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The Senior Big Data Architect & Analytics Engineer will design and implement complex big data solutions while collaborating with stakeholders. The role requires expertise in Spark, Kafka, SQL, cloud platforms, HDFS, and the Elastic Stack.
Design and build scalable AWS-based data lakes and ingestion pipelines, bridging data engineering and science to enable analytics and insights.
The Data Analytics & AI Insights Engineer will transform complex data into business insights by managing end-to-end analysis, creating advanced dashboards, and applying data science and machine learning techniques.
The AWS Data Architect will design and implement data ingestion solutions and scalable pipelines on AWS. This role bridges data science and data engineering teams to enhance cloud-native data platforms.
The AWS Data Architect designs and optimizes scalable data ingestion pipelines and data models using AWS services like Redshift, RDS, and DynamoDB. The role involves bridging data science and engineering teams while mentoring junior staff and participating in client workshops.
Designs and implements AWS-based data solutions, bridging data science and engineering to build scalable data pipelines, models, and operations while advising teams on best practices.
AWS Data Platform Engineer at NTT DATA building data acquisition, transformation, and loading pipelines into AWS data lakes for analytics and ML, along with CI/CD pipelines and monitoring using AWS tools.
The Data Architect will design, build, and secure scalable batch and real-time data pipelines on the Google Cloud Platform. The role focuses on ensuring reliable data delivery to support data-driven decision-making across the organization.
Designs and builds cloud-native Azure data platforms to process raw data into insights for analytics and machine learning, ensuring security and scalability.
The Big Data & Analytics Engineer will design and implement scalable big data solutions while collaborating with international teams and clients. The role requires proficiency in Spark, Kafka, SQL, REST APIs, and cloud environments.
The Data Architect will design, build, and maintain secure, scalable data processing systems and lead large-scale data pipelines on Google Cloud Platform. The role focuses on transforming raw data into actionable business insights through efficient data integration.
Design, build, and operationalize scalable data processing systems on Google Cloud Platform, turning raw data into actionable insights using Python/Scala/Java, BigQuery, and ELT approaches.
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The AWS Data Architect will design and implement data pipelines and lake solutions on AWS, collaborating with analysts and solution architects to support data platform projects. The role requires strong coding skills and expertise in data ingestion and modeling within cloud-native environments.
The Data Architect will design, build, secure, and monitor real-time and batch data processing systems using Google Cloud Platform services. The role focuses on creating scalable and reliable data pipelines to transform raw data into actionable business insights.
Design and operate scalable, secure data processing systems on GCP, building large-scale batch and real-time ELT pipelines with BigQuery and Dataflow using Scala, Java, or Python.
The AWS Data Platform Engineer will design and optimize data lake solutions, manage data pipelines, and implement CI/CD and monitoring on AWS. The role involves collaborating with architects to support analytics and machine learning initiatives.
The Big Data Architect & Engineer will design and implement complex data intelligence applications using Big Data technologies. The role requires proficiency in Spark, Kafka, NoSQL, SQL, and object-oriented programming languages like Java, Python, or Scala.
Designs and implements complex big data solutions using Spark, Kafka, and cloud platforms, analyzing requirements, estimating timelines, and advising on technical choices.
The Senior GCP Data Architect & Engineer will design, build, and monitor data processing systems using Google Cloud Platform tools. The role focuses on transforming raw data into actionable business insights through scalable, real-time ELT pipelines.
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