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The thermal engineer troubleshoots thermal and/or airflow issues in new and existing product lines using empirical data and commercial CFD software. Work with the engineering team to optimize the thermal performance of servers using empirical data and bench test methods.
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Experience with data warehousing, data lakes, and data pipelines, with experience in Snowflake, AWS, Google Big Query, Airflow preferred. The Sr. Technical Product Manager will also be responsible for working with cross-functional teams to ensure that data is used effectively across the organization in close partnership with data engineering, data science, and strategic insights teams.
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The Director Software Engineering will be part of a global data/software development team that focuses on building scalable and optimized business intelligence reporting to satisfy Strategic Advisers business needs.
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Experience with performing other analysis such as Finite Element Analysis (FEA) and Data Center cooling simulations. You’ll also work cross-functionally with Hardware Engineering, Product Management/Marketing, Product Operations, Global Supplier Management (GSM), External Vendors/Suppliers, Manufacturing Operations, and EMS/JDM partners.
$162,000 - $238,700Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Experience with cloud-based data warehousing solutions like Snowflake and data engineering platforms like Databricks. 5+ years of professional experience in software development with familiarity in data engineering or data science.
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5+ years of hands-on experience in two or more database technologies (e.g., MySQL, PostgreSQL, MongoDB) and data warehouses (e.g., Redshift, BigQuery, or Snowflake), as well as cloud-based data engineering technologies (e.g., Kafka, PubSub, Apache Airflow, Glue.
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Expert level understanding of cloud data platforms (AWS, GCP, Azure) and large scale data processing using traditional and distributed systems with tools like Airflow and Spark. This position is tailored for an experienced professional who can seamlessly transition between the responsibilities of a Data Engineering Manager and a Senior Data Engineer, based on their unique skill set and aspirations.
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Work with a state-of-the-art data technology stack (Spark, Tensorflow, Pytorch, Snowflake, Airflow, AWS Ecosystem) that operates in the cloud to empower predictive modeling services for both internal and external customers.
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As a Staff Engineer on the Data Transmission Engineering team, you will develop and maintain the services and tools powering HealthVerity's data pipelines. Python, Spark, Hive, Hadoop, Serverless Framework, Postgres, React, AWS Lambda, AWS ECS, AWS SNS/SQS, AWS Eventbridge, Airflow.
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Proficiency in ML Ops and ML Engineering frameworks: experiment trackers (like mlFlow) & orchestrators (Airflow, Kubeflow, Sagemaker Pipeline) Based in Paris or Barcelona, you will be part of the Artificial Intelligence Engineering team, in the Group Emerging Technologies and Data (GETD) division of AXA. This transversal team’s mission is both to build AI-powered initiatives (proofs of concept, proofs of value, pilots) with AXA entities & strategic partners and to define & implement MLOps best practices, tools, and collaboration models to be followed across the whole AXA Group.
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Python, pyspark, snowflake, data bricks, Airflow, Gitlab, Linux. Sigmoid brings deep expertise in data engineering, predictive analytics, AI/ML, and Data Ops. You will be part of the technology function for Marcus, focusing on building and managing our data engineering architecture that enables the business to operate efficiently.
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This is a great opportunity to join a global dynamic team where you will learn both - 1) developing world class engineering solutions, including cloud computing and big data analytics, designing technical solutions for complex problems, optimized storage management, self-service toolkits, building compelling visualizations using web components as well as 2) business functions that Goldman offers its clients.
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Build complex data engineering pipelines using Python and Airflow to hydrate datamarts in Snowflake and Data Lake in AWS Cloud. Minimum 7 years of related experience in data engineering.
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Minimum 10 years experience in Data Engineering and Lead experience atleast 3-4 years. Experience with Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet), Kafka, Spark Streaming, PySpark, Airflow.
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Experience in Data/ML Pipelines using S3, Athena, Glue, Airflow, Kinesis or Kafka, and Sagemaker. Five (5) years of experience in software and/or data engineering. Our approach couples the latest technology with engineering expertise and analytical proficiency while remaining true to genuine customer relationships and a culture that fosters growth and opportunity.
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