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You will work with the open source community to enable Apache Spark data processing with GPUs. Data workflows can benefit tremendously from being accelerated, enabling data scientists to explore many more and larger datasets to achieve their business goals, faster and more efficiently.
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Experience with streaming / data processing technologies such as Beam, Spark, Kafka, Airflow, HBase, Presto. Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, Presto, HBase.
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We are currently seeking a Data Technical Lead (Apache Spark, Pyspark and Databricks) to join our team in Dallas , Texas (US-TX) , United States (US). Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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Direct hands on experience with highly scalable data pipelines using BigData technologies (Spark, Hive, Airflow, DBT, Parquet / ORC, Kafka / Streaming, etc) 8+ years of professional data engineering or software engineering experience, with a focus on heterogeneous, large-scale data processing for machine learning pipelines.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Inside-out understanding of at least one major distributed data processing framework (Spark, Dask, Ray, Our primary developer offering is an ultra-performant Data Processing Framework (unified streaming + batch) with a Python API, distributed Rust engine, and capabilities for data source integration & transformation at scale (Kafka, S3, databases/CDC.
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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.) 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.
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Familiarity with cloud-based data storage and processing technologies for handling large datasets efficiently. 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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You will be working with all levels of technology from backend data processing technologies (Databricks/Apache Spark) to other Cloud computing technologies / Azure Data Platform.
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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. Explore and build proof of concepts using open source NOSQL technologies such as HBase, DynamoDB, Cassandra and Distributed Stream Processing frameworks like Apache Spark, Kafka stream.
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Strong mathematical background with strong knowledge in at least one of the following fields: statistics, data mining, statistics, operations research, econometrics, and/or information retrieval (image processing (OpenCV) and natural language processing is a plus.
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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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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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5+ years of experience using AI/ML , data science software (e.g., Python-based tools) Knowledge of data preprocessing, feature engineering, and model evaluation techniques in machine learning projects.
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