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Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark. Solid understanding of foundational concepts and algorithms in statistics and machine learning, including NLP, linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, reinforcement learning, etc.
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We are hiring a talented Senior Data Engineer in roles related to building cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development.
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Apache Kafka, Apache Flink, Apache Spark, Trino (Presto), Apache Airflow/Dagster, Apache Superset, AWS S3, Snowflake, Amplitude, CDP (e.g. Segment.com) The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs and various Data Science and Analytics related tooling.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Proficient in Databricks, Python, Pyspark, Scala for developing and maintaining data engineering pipelines, with expertise in Apache Spark, Flink, and containerization. Expertise in architecting, designing and building data pipelines and acquiring data needed to build and evaluate models, using tools like Databricks, Dataflow, Apache Beam, or Spark.
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Advanced knowledge of cloud computing technologies such as Apache Spark, Azure Data Factory, Azure DevOps, Azure Client (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Proficiency with deep learning tools and at least one machine learning tool, such as Hadoop, Apache Spark, TensorFlow, scikit-learn, or cloud-provider equivalents. Proven ability to work with at least one machine learning tool like Hadoop, Apache Spark, TensorFlow, or scikit-learn, or cloud-provider equivalents.
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Responsibilities and Contributions Organizational and Leadership Role Coaches and mentors others by example and through direct coaching on machine learning and artificial intelligence skills.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. The search team comprises the e-commerce search platform, backend services, machine learning endpoints, and our search engine, which enables grainger.com customers to findproducts that serve relevant content to online customers, internal support teams, and marketing programs.
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Big Data & Distributed Systems : Hands-on experience with Apache Spark for distributed data processing, PySpark , or Spark MLlib for scalable machine learning. Real-Time & Batch Processing : Knowledge of building real-time data pipelines using Apache Kafka and batch pipelines with Apache Spark or Airflow.
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Proven leadership experience in data engineering and machine learning engineering roles, with extensive experience leading remote-first teams. Oversee the design, development, and maintenance of data infrastructure using platforms like Snowflake, Adtran, Databricks, SQL, COSMOS DB, Apache Kafka, Hadoop, Spark, DBT (Data Build Tool) and cloud data services (AWS, GCP, Azure.
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Design, implement, and maintain complex ETL pipelines using tools such as Apache Spark, Apache Airflow, and AWS Glue for both batch and near real-time data processing. Expert knowledge of distributed data processing frameworks like Apache Spark, Hadoop, or Flink.
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In-depth knowledge of Apache Spark and Databricks architecture. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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Skills: DB2, Informatica, Jenkins, Snowflake, Openshift, Apache Spark, AWS, PostgreSQL, Git, Node.js, PySpark, SQL, Amazon Kinesis, Java, Python, Shell Scripting, Cucumber, EKS, MongoDB, Angular, Docker, Atlassian Suite, SAS.
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Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML. Experience with Big Data platforms such as Databricks or Apache Spark.
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