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Minimum of 10 years of experience in big data, database and data warehouse architecture and delivery. AWS services, big data, data warehouse architecture, Certified AWS Big Data Specialty (Nice to have.
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Design, develop and deliver data integration/data extraction solutions using IBM DataStage or other ETL tools and Data Warehouse platforms like Teradata, BigQuery. GCP Data Engineer.
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You will work with highly committed and high-performing teammates to deliver a best-in-class solution leveraging cutting-edge technologies in the area of Big Data, Visualization, and Insights, Advanced Analytics.
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Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalog etc. Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
$55 - $60 an hourExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Job Role: GCP Data Engineer. 1-2 years of experience in Google Cloud Platform (especially Big Query). Knowledge of data Modelling, database design, and the data warehousing ecosystem.
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MarTech and big data knowledge is preferred in the digital space (DMP, digital identity solution, data clean room, CDP, etc.) Strong written and oral communication, data visualization, presentation, and interpersonal skills.
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Analytics: Fluent with SQL, PL/SQL and have used analytics tools like Big Query for data analytics. Cloud experience: Experienced in GCP services like cloud function, cloud run, data flow, data proc and big query.
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In this role, you will research and apply engineering best practice and latest technology to lead physical design for data layers, evolve ways of working to support rapid growth in data inventory as well as variety and number of deployed data science applications.
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Python, SQL, Looker, Redshift, Big Data, cloud computing (especially AWS). Extensive experience with the following technologies: SQL, Looker, Redshift, Big Data, cloud computing (especially AWS.
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Experience developing data engineering and ML pipelines in Databricks. Write Python code in Databricks Notebook for data preprocessing, processing unstructured data/documents, feature extraction, API calls, and application orchestration.
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Big Data Technologies: The data scientist has knowledge of big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks. We are looking for someone with experience with AWS Client and AI tooling, along with distributed computing tools such as DataBricks, Comprehend, and SageMaker; data visualization.
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Strong understanding of regulatory requirements and compliance issues affecting clients related to privacy and data protection, such as PCI DSS, GLBA, Basel II, EU Data Protection Directive, International Cross Border, and U.S. State Data Privacy Laws.
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Solid Understanding of Clinical Terminology such as SNOMED, ICD9/10, CPT, HCPCS, READ Solid understanding of healthcare data, particularly electronic health records (EHR) and insurance claims, and experience working with healthcare data standards.
$201,025 - $260,150 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience in working with Machine learning and AI concepts related to RAG architecture, LLMSs, embedding and data insertion into a Vector data store. To thrive in this role, you should have ten-plus years of experience in architecture, design, and building a scalable target state architecture for data processing-based on document content including PII/CII handling, policy-based hierarchy rules and Metadata tagging.
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We are seeking a highly skilled AWS Data Engineer with expertise in building Data pipelines and processing solutions on the AWS platform, focusing on Databricks, Delta Lake, and Python development.
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big data jobs Title: technology lead Company: Tiger Analytics in Whippany, NJ
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