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Expertise in big data technologies like Hadoop, Apache Spark (Scala preferred), Apache Hive, or similar frameworks on the cloud (GCP preferred, AWS, Azure etc.) Experience building complex near real time (NRT) streaming data pipelines using Apache Kafka, Spark streaming, Kafka Connect with a strong focus on stability, scalability, and SLA adherence.
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The Director of Finance and Administration (DFA) has a primary reporting relationship to the Chair of Department of Biomedical Data Science, with a secondary reporting relationship to the Associate Dean/Chief Financial Officer for the School of Medicine, which ensures organizational alignment between DBDS’ strategy and the broader SoM mission.
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Must have a technical background and be able to lead data integration, data modeling, MDM workflow, etc. Good understanding replication framework with Data transfer, ALE/IDOC, Key & value mapping, MDG Export & import master data and conversion of master data.
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A proven track record in building and maintaining big data platforms for streaming and batch data processing, data engineering, building backend systems and APIs. Partner with data scientists, data analysts, fraud specialists, infrastructure engineers and product managers to design, build and deliver big data projects and new data platform capabilities.
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By fusing cutting-edge machine learning, data analysis, and interactive visualization technologies, we research and develop scalable and transparent AI & big data analytic solutions (e.g., audio, images, sensor logs) for a range of domains, including Industry 4.0 (I4.0), IoT, autonomous driving, and connected vehicles.
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Lead Data Scientist: Master's degree with over 5 years of industry experience or PhD with over 2 years of industry/research experience. Strong experience using key Python packages for data wrangling, machine learning and deep learning such as pandas, sklearn, TensorFlow, torch, transformers, LangChain, etc.
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The core focus areas for the Satellite Software Team include mission software (radar data collection, storage, processing, and downlink), radio communications, satellite/flight control, telemetry, and embedded firmware.
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As a Principal Software Engineer, you will partner with the Engineering Director in leading technical direction, architecture and usage of Native Google Cloud technologies such as Big Query, Big Table, Data Flow, and Looker.
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Must have expertise in NX/other CAD data migration from legacy system/s to Teamcenter PLM. Several full CAD data migrations. Must have in depth knowledge on Teamcenter PLM architecture and data import - export utilities from data migration perspective.
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Proficient with querying and manipulating big datasets on AWS Athena, BigQuery, and MySQL. Hands on experience with ETL automation. Professional experience with SQL and data visualization tools (Tableau, Power BI, etc.
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Experience with multiple big data solutions such as DynamoDB, MongoDB, BigQuery, Databricks, SnowFlake, etc. Develop and lead the technical vision for creating complex data products at scale.
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Experience with data warehousing, business intelligence (BI), data governance, data architecture, data integration, data classification, data strategy, data quality management, data security and privacy, metadata management, data standards, regulatory compliance, and enterprise architecture frameworks.
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Lead and manage a small but high-performing team of data engineers, machine learning engineers, and automation specialists. The Enterprise Data Transformation and AI/ML will be responsible for providing strategic leadership and direction in the development, implementation, and optimization of Enterprise Data Strategy and Artificial intelligence (AI), machine learning (ML), and automation initiatives within the organization.
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Big Data Tools: Kubernetes (K8s), Hadoop, Spark, Postgres, Databricks, Azure cloud offerings including (Azure Synapse, ADLS, Azure Functions) Design and build an HR data platform, based on modern data warehousing/lakehouse practices, integrating data from multiple source systems, including cloud and on-premises applications such as Workday, employee listening tools, learning systems and broad HR technology stack.
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Familiar with backend systems such as MySQL/Redis/Nginx/Kafka/Kubernetes/Docker and big data technologies such as Hadoop/Spark/Flink/Hive/OLAP/ClickHouse, etc. Manage day-to-day operations of data service, realtime/batch data pipelines, such as SLA management, system deployment, performance tuning and trouble shooting.
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big data jobs Title: lead in Palo Alto, CA
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