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Demonstrating relevant project management experience in organizing and leading teams including Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development (tools: IICS/AWS Glue/SAP BODS/ SSIS/SnapLogic); preferable in P&C Insurance data warehouse.
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Human-Centered Data Science (e.g., databases, big data, information retrieval, robotics, artificial intelligence, information visualization) Cultural Heritage Informatics (e.g., archives, digital collections, preservation, digital curation, digital humanities, museum studies, metadata, cultural studies of information technology, history of information, critical data studies.
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You will assist clients in choosing a platform, defining their data needs and migrating them to a modern cloud data environment using cloud providers such as Azure, Google Cloud Platform, Amazon Web Services, Snowflake, Databricks or Teradata.
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Being highly organized; Proven track record of implementing cloud data architecture and data integration patterns (AWS Glue, Azure Data Factory, Event Hub, Databricks, etc.) Implementing enterprise data solutions concepts such as Master Data Management, Data Governance and Enterprise Data Warehouse.
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Continuously update your knowledge of Analytics and Data Engineering trends, particularly in AWS, Redshift, Snowflake, Python, SQL, and dbt, to enhance our technology stack. You will utilize your deep expertise in Python, SQL, ELT processes, AWS, Redshift, and Snowflake to create and optimize data solutions that adhere to best practices in software engineering.
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Understanding of Data Warehousing concepts (normalization, OLAP, OLTP, Vault data model, graphs, star & snowflake schemas); Understanding and familiarity of one or more is a big plus - CI/CD, cloud devops, containers (kubernetes/Docker, etc.
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3+ years of experience with data applications and tools (Snowflake, Databricks, Spark, EMR, Presto, Datadog, DBT, etc.) We power the technology, data enablement, and convergent marketplaces required to ensure buyers and sellers can transact across all screens, across all data types, and all sales channels to ensure results for marketers.
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Cloud: AWS or Azure or GCP in Data Engineering and Analytics streams. Familiarity in Data Engineering tools, data ops tools in On-prem and Cloud eco system. Familiarity with one of the Data Governance & Data Catalog tools.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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Architect, design, and code shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across the Data organization. Maintain detailed documentation of your work and changes to support data quality and data governance requirements.
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The Data Capture team for the Data organization within the DE&ET organization is in search of a Lead Software Engineer. 2+ years of data engineering experience developing large data pipelines.
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Graduate Big Data Analytics Natural Language Processing Machine Learning Data Mining Cybersecurity Cyber-Human Systems. The College stands out for its leading research in areas such as artificial intelligence, data analytics engineering, cybersecurity engineering, biomedical imaging and devices, community-based healthcare, autonomous systems, 5G/Next G communications, systems architectures, computational biomedicine, advanced materials and manufacturing, sustainable infrastructure, and more.
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As a member of the Data Capture team you will establish the foundational set of core platform frameworks and pipelines which are a vital key to success – enabling dozens of engineering and analytical teams to unlock the power of data to drive key business decisions and provide engineering, analytics, and operational teams the critical information necessary to scale the largest streaming service.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Ensure high operational efficiency and quality of the Data Capture platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams.
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big data jobs Company: Teksystems in NJ, Oregon
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