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Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, Presto, HBase. Experience with streaming / data processing technologies such as Beam, Spark, Kafka, Airflow, HBase, Presto.
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Keywords : GCP, Google Cloud Platform, BigQuery, Composer, SQL, Python, Data Engineering, Data Pipelines. Experience working with GCP technologies like BigQuery, Composer, GCS, DataStream, Dataflows.
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You have worked with Dagster/Airflow, BigQuery, GCP, Terraform, Kubernetes, sklearn, keras/TensorFlow/pytorch, dbt, data modeling, Python/Pandas data frameworks, and scalable technical concepts/solutions.
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Desired experience in: Looker / Google Data Studio, BigQuery, Apache Airflow / Google Cloud Composer. Experienced with BigQuery or other data warehouse products. Experience with other modern programming and scripting languages are a plus (e.g. R, Spark, Javascript, Java, UNIX Shell scripting, Perl, Ruby, etc.
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Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.) Strong proficiency in programming languages such as Python, Java, or Scala, with expertise in data processing frameworks and libraries (e.g., Spark, Hadoop, SQL, etc.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Expertise in open source data science technologies such as Python, R, Spark, SQL.
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Our stack spans AWS and GCP, with technologies like Airflow, Redshift, BigQuery, Postgres, Spark, and dbt. Standing up a reporting system in BigQuery from scratch, including data replication, infrastructure setup, dbt model creation, and integration with reporting endpoints.
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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Bachelor's Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT.
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Experience with public cloud environments(AWS, Azure, GCP), preferably experience with Google Cloud services like Bigquery, GCS, Cloud Composer, PubSub. Experience with big data tools: Hadoop, Spark, Kafka, Spark & Kafka Streaming, Python, Scala, Talend etc.
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A true one-stop shop, offering a full portfolio of electrified and internal combustion vehicles designed to integrate seamlessly with the Ford Pro ecosystem, helping customers' businesses thrive today and into the new era of electrification.
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B. Kafka, Spark, Snowflake, GCP, BigQuery, Java, Python, SQL, Airflow und gängiger Data-Science-Libraries und -Tools. B. Kafka, Spark, Snowflake, GCP, BigQuery, Java, Python, SQL, Airflow und gängiger Data-Science-Libraries und -Tools.
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Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply.
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Familiarity with cloud data storage solutions such as AWS S3, Google Cloud Storage, Azure Blob Storage, AWS Redshift, Google BigQuery, Azure SQL Data Warehouse, or others. Experience with cloud data processing and analytics services such as AWS Glue, Google Dataflow, Apache Spark on cloud platforms, or Azure Data Lake Analytics.
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Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt. Familiarity with modern ETL tools such as Apache Beam, Kafka, Spark, or similar. Experience with Scala and Spark or PySpark.
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