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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. Sight and Sound play a large role in our day-to-day experiences.
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Proficient in designing and implementing data processing pipelines using Azure DataBricks and Azure Data Factory. Code and debug user interface, API, batch-oriented file processing, high-availability applications, and data warehousing.
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Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark. Drive best demonstrated practices in software engineering, and share learnings with team members in AAG about theoretical and technical developments in ML engineering.
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As a lead engineer with Retail, Site Reliability Engineering team, you will be at the forefront of Cloud and Big Data technology. Maintain data integrity and access control by using AWS security tools and services such as HSM, IAM, etc.
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Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows.
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6-8 years of Data Engineering experience working with both distributed architectures, ETL, EDW and Big Data technologies. Experience with Google Cloud Services such as Streaming + Batch, Cloud Storage, Cloud Dataflow, Data Proc , DFunc, Big Query & Big Table.
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8+ years of experience in data engineering roles, preferably with Snowflake, dbt, GCP, and Python. Familiarity with Google Cloud Platform (BigQuery, Dataflow, Cloud Functions) for data processing and storage.
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The Big Data Software Engineer will define and implement pipelines for the ingesting, storing, processing, and analysis of data. Experience with ETL processing of big data sets.
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Developing and deploying machine learning pipelines using Vertex AI and Kubeflow for data processing, feature engineering, model training, evaluation at scale in production on GCP ensuring data quality, integrity, and security.
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Experience with version control systems (e.g., Git) and CI/CD processes in data engineering. Bachelor's degree in Computer Science, Data Engineering, or a related field. Stay up-to-date with the latest technologies and trends in data engineering and analytics, continually improving existing processes and infrastructure.
$80 an hourFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka. Solid experience implementing data lineage, data quality and data observability for big data workflows.
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Implement cutting-edge AI/ML techniques, including Generative AI, to boost the efficiency of the platform and data engineering processes. You’ll build a deep understanding of our digital streaming service and use that knowledge, coupled with your engineering, infrastructure, data, and cloud knowledge, to optimize and evolve how we understand our technical ecosystem.
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Finance, Business Administration/Management, Economics, Statistics, Computer and Information Science, Management Information Systems, Engineering, Data Processing/Analytics/Science, Mathematics, Accounting.
$232,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Stream Processing: Experience with Apache Kafka, Apache Spark or similar for real-time data processing and stream analytics. Leadership: Lead by example within the data engineering team, taking pride in your team’s deliverables, and performing as technical lead for a scrum team or on various projects, where applicable.
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5+ years of experience in data engineering with proficiency in Snowflake, dbt, and GCP services (BigQuery, Cloud Storage, Dataflow). This role involves building data pipelines with Snowflake, dbt, and Google Cloud Platform (GCP) while utilizing Python for data processing and automation.
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big data engineering image processing jobs in Atlanta, GA
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