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Any experience with AWS Cloud, AWS Glue ETL, Databricks Delta/Redshift/ Talend Big Data would be added advantage. Design and build scalable data pipelines using Big Data stack Databricks, Spark Scala, AWS – Athena, S3, Glue ETL, Redshift, Dynamo DB.
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Work with big data technologies like Azure Databricks, Apache Spark & Palantir. 8+ years of experience in data engineering, machine learning, and cloud tech developing production grade software components and solutions.
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Lead a group of engineers building data pipelines using big data technologies (Spark, Flink, Kafka, Snowflake, AWS Big Data Services, Snowflake, Redshift) on medium to large scale datasets.
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At least 2 years of experience in big data technologies. 4+ years of data warehousing experience (Redshift or Snowflake) Build the next generation Distributed Streaming Data Pipelines and Analytics Data Stores using streaming frameworks (e.g. Flink, Spark Streaming, etc.
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Solid experience implementing data lineage, data quality and data observability for big data workflows. Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka.
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Must have extensive hands on experience in designing, developing, and maintaining software solutions on Big Data platform such as Hadoop eco-system. Must demonstrate expertise in data migration best practices from on-prem to Cloud with technologies like Hadoop and Azure cloud with Databricks platform.
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Bachelor's Degree in Computer Science, Engineering, Management Information Systems (MIS), Business or related\/relevant degree AND minimum of 2 years of experience as a Data Engineer, Integration Developer, Database Developer, BI Developer, Software Engineer, Programmer, Technical or Systems Analysts, and\/or Database Administrator preferred.
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Expertise in architecting, designing, and building end to end data platforms in the GCP environment using BigQuery and other services while adhering to best practices guidelines such as open standards, cost, performance, time to market and minimize vendor lock.
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10+ (for senior) 15+ (for principal) of proven experience in modern cloud data engineering, data architectures, data warehousing, and software engineering. Solid experience designing and developing modular, distributed data platform components with a microservices architecture.
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From large scale mass communication projects to highly secure and confidential data analytics using Big Data frameworks like Hadoop and AWS Redshift, ODS has a broad set of proven technical capabilities that help companies make complex digital transformations.
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Experience interacting with various database and file storage systems (DB2, IDMS, Oracle, Hadoop, NoSQL), data manipulation language (i.e. SQL), and/or data visualization tools (i.e. Tableau, Power BI.
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Experienced in developing large scale enterprise applications using Big Data open-source solutions such as Hadoop, Spark, Kafka, and Elastic Search. Designing and developing distributed applications using Big Data technologies such as Hadoop, Spark, Kafka, and Elastic Search.
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Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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Internet of Things, Artificial Intelligence, Cloud Computing, Software as a Service (SaaS), Internet of Things (IoT), Artificial Intelligence (AI), Automotive, Big Data. Execute the complete model life cycle: data identification, cleaning, EDA, model training, validation, and deployment.
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Help design data models to support an agile development lifecycle inclusive of data visualization and predictive analytics. Partner closely with data engineering to ensure on-time delivery of data relevant to the roadmap.
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big data jobs Title: hadoop consultant Company: Joveo Us in Plano, TX
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