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Fluent in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting.
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Conduct in-depth data analysis using Python, MATLAB, and relevant tools to address complex problems, define key performance indicators for autonomous vehicle systems, and effectively communicate analytical insights to stakeholders.
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Advanced experience with Azure using data warehouse technologies, including Azure Data Factory, Azure Synapse, Azure Synapse Analytics, Azure SQL DB, Azure Logic Apps, and Azure Analysis Services, Azure Databricks.
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Over 8+ years of professional experience in roles such as Data Engineer or Developer, showcasing a strong technical command over Snowflake, dbt, Airflow, SQL, and other pertinent technologies. Conceptualize and construct resilient, high-performance data solutions utilizing Snowflake, dbt, Airflow, and SQL Server to fulfill organizational objectives.
$200,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a data engineer, you have experience spanning traditional DW and ETL architectures and big data ecosystems like Databricks / Snowflake / EMR / Airflow. Role DescriptionDropbox is looking for a Data Engineer to join our Finance Data Engineering (FDE) team to build out next generation Financial data pipelines that power crucial business decisions throughout the organization including metrics (ARR, Churn) that are reported externally to Wall St. The team is responsible for curating Gold Datasets (user, team, product etc) that are the source of truth for analytics and operations at DropboxDo you dream about Data and talk to your friends in SQL.
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Experience with the Big Data technologies is a plus (Redshift, Hadoop, M/R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink etc) Design and optimize the big data architecture, including data collection, data governance, data security, data warehouse, data application, algorithm application etc.
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The Data Coordinator is responsible for Student Information System (SIS), CALPADS and attendance related tasks, including creating reports and maintaining student data for Charter Impact clients.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Industry recognised badges and certificates on any of the following tools: Snowflake, Azure Synapse/Data Factory, DBT Cloud, Azure DevOps, PowerBIwould be beneficial. Proficient across many domains of data engineering, including ELT/ETL, metadata management, data integration, data management in transit and at rest and data streaming.
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Reporting to Dr David Levine, the Data Scientist will work across all phases of the research project, including extraction and organization of clinical and other data from a variety of information systems, automated data cleaning and verification, design, administration and construction of databases, analysis using valid statistical approaches, and development of new informatics and clinical tools.
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Developing and maintaining data warehouses in big data solutions e.g., Snowflake; developing solutions on cloud computing services and infrastructure in the data analytics space; leading the implementation and deployment of emerging tools and process for data engineering to measure quality; partnering with machine learning and business intelligence engineers to develop strategic enterprise projects.
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Connect our production backend / data to business systems including salesforce, marketo, intercom, google analytics, metabase, etc. Innovate, design, and build data systems, services, and tools using GCP (Google Cloud Platform) that scale with OneSignal’s products and business requirements.
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The Smithsonian Institution’s Office of Advancement seeks a Data Engineer to serve as a key member of the Advancement Technology Services team as we transform our data management approach.
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Familiarity with cloud data platforms (e.g. Databricks, Snowflake, Azure, GCP, AWS) and big data technologies are a plus. Proven track record of success in startup sales environments, with experience in selling enterprise based AI-powered solutions or data operations platforms preferred.
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Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks. Knowledge of Python data science tools, such as SciKit, Numpy, TensorFlow, Jupyter.
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data job Title: associate Company: Stanford Medicine
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