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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Build programs that control the flow of data, model processing and output generation, and integration to the rest of the analytics platform using big data tools such as AirFlow, DataFlow, and DBT.
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Minimum of FOUR (4) years of hands-on experience implementing Collibra data catalog, data governance, data lineage, data privacy, and data quality capabilities.
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Master’s degree in data science, business, sciences statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field (MBA Preferred.
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With integration platform architecture (conceptual, logical, and physical), developing interface design, data mapping, and integration deployment. Define standards and procedures for data modeling, database design, reference data management, and integration requirements and design.
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6 years of experience must include: Ab initio, Informatica, Data Stage; Teradata, IBM DB2, Cognos, Oracle PL SQL; Autosys, Control-M, Erwin, XML, HTML, CSS, Unix Shell Scripts; Data Analysis, Data Processing, Code Optimization, Performance tuning; Automating Business Process and Models; Microsoft Visio, Web Services, Crystal Reports; and HP Quality Center, ALM, VSS, EME, XSD. At least 3 years must include: Hadoop, HDFS, Big Data, Hive, Spark.
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Specifically, this experience must be in writing Big Data data engineering jobs for large scale data integration in AWS. Prior experience in writing Machine Learning data pipeline using Spark programming language is an added advantage.
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The Data Integration Engineer will also develop and deploy tools for real-time analysis and visualization of all relevant end-to-end process and analytical data and metadata to enable a fully integrate process and analytical data workflow.
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Sr. Data Engineer Onsite -Troy Michigan-Open to c2c Duties and Responsibilities: The Sr. Data Engineer is responsible in understanding and supporting the businesses through the design, development, and execution of Extract, Transform, and Load (ELT/ETL), data integration, and data analytics processes across the enterprise.
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Design and develop integration capabilities between Informatica MDM and various data sources/systems including on-premise and AWS cloud environments using IICS, Power Center, IDQ, Web services and other integration mechanisms and patterns.
$103,000 - $155,000 a yearFull-timeExpandApply NowActive JobUpdated 4 months ago - UpvoteDownvoteShare Job
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These technologies may include artificial intelligence, machine learning, statistical techniques, mixed integer linear programs, reporting/big data analysis, dashboarding, data integration, and other heuristics/algorithms.
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Must have extensive experience in ETL development, Data Ingestion and Data Integration using API/microservices based approach. Ability to lead solution for Data Quality, Data Profiling, Data Catalog and Metadata management strategy.
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Required 10 Years Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL, Azure Synapse Required 5 Years Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL Required 10 Years Hands-on experience in Azure SQL Database, Azure SQL Datawarehouse Required 7 Years Hands-on experience in deploying and maintaining large-scale data processing pipelines.
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Experience using Microsoft Azure and Databricks (for example, PySpark SQL and Dataframe) to perform data mining and EDA. Mine and analyze data (both structured and unstructured data) from company databases and external data when needed to drive quality improvement, process optimization and business strategies.
$92,400 - $147,800 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Our tenant is a strong cross-domain team to deliver E2E solutions covering tech areas ranging from machine learning, big data, microservices to data visualization. 3+ years of big data development experience with technical stacks like Spark, Flink, Singlestore, Kafka, Nifi and AWS big data technologies.
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