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Strong hands-on experience in Workday technologies - Enterprise Interface Builder (EIB), Advanced Report Writer, Cloud Connect (PICOF, PECI, CCW, CCB), Business Process Framework, Configurable Security, Calculated Fields, Custom fields, XML/XSLT, Studio, BIRT Reporting & data analytics.
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Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google, security certifications) Presentation skills with a high degree of comfort with both large and small audiences (Senior Executives, Management, Data Scientists, Engineers, etc.
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Hands-on Experience in Big Data and cloud technologies tools, i.e. Hadoop, Hive, Iceberg, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes. The Data Science and Machine Learning team at Lucid is on the mission to design, develop, and deploy AI solutions to help make safe and sustainable products and services on par with Lucids Luxury brand.
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You will be a key contributor for our Ediscovery Platform and responsible for both hands-on technical work to improve existing systems as well as guiding long-term enhancement and evolution in this space.
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Search and NLP : Hands-on experience with search engines like ElasticSearch and NLP tools like Langchain desired. Experience : 3-5 years of hands-on experience in software engineering with a focus on data-centric and distributed systems applications.
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Hands-on development experience in Microsoft Power BI tools. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations.
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Hands-on experience with cloud-based platforms and services, such as OCI, AWS, GCP, and Azure. Experience deploying LLM models in cloud environments (e.g., OCI, AWS, Azure, GCP) and on-premises infrastructure.
$96,800 - $251,600 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Hands-on experience on running distributed Splunk cluster infrastructure and all related components - In-depth knowledge on Splunk search processing language (SPL) and visualization.
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Developing APIs for consuming AWS cloud resource using the SDKs. Developing scripts for using AWS Lambda to migrate and capture the change data for Legacy systems to DynamoDB. Writing complex parallel streams and filters to refine the data for effectively handling the client search.
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Hands on experience with one or more of the IaC development and deployment (ARM, Bicep, Ansible, etc.) Design and implement cloud services for DT projects using Microsoft Azure based on business requirements, ensuring scalability, reliability, and security performance.
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Advanced Data Processing: Experience with algorithmically intensive data engines operating on streaming, large, multi-tenant datasets. Experienced: 7+ years of relevant experience in backend engineering, with a substantial focus on data-intensive platforms.
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5+ years of hands-on experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc., and hands-on experience with Python programming and statistical packages, and ML libraries such as scikit-learn, Keras, TensorFlow, PyTorch, MXNet, etc.
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Ideally 5+ years of hands-on design and development experience in several of the relevant technology areas (GitLab, Terraform, Azure, ADO, Azure Data Lake, Azure Kubernetes Service, Spark, Databricks etc.
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Deep working knowledge on GCP cloud platformand solutions in infrastructure, Applications or Data technologies (GCP) Designing, architecting, implementing, andmanaging cloud infrastructure on Google Cloud Platform.
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Hands-on experience with database systems (e.g. SQL, NoSQL, vector, search) and data warehousing solutions (e.g. Snowflake, Redshift, BigQuery) Manage and optimize AWS cloud-based data infrastructure including storage, compute, and networking resources.
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