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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). In-depth knowledge of Apache Spark, Pyspark and Databricks architecture.
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Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka. As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications.
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AWS Cloud Engineer w/ Machine Learning Ops. Experience with building data pipelines in getting the data required to build, deploy and evaluate Client models, using tools like Apache Spark, AWS Glue or other distributed data processing frameworks.
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Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark, Snowflake?) A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions.
ExpandApply NowActive JobUpdated 16 days ago - UpvoteDownvoteShare Job
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AWS Secrets Manager, AWS Certificates Manager, JBoss, Apache HTTPS, AWS Security Hub, Crowdstrike, Red Hat Enterprise Linux (RHEL), Red Hat OpenShift or other Kubernetes platforms. AWS Management and Government services, Past experience in supporting highly available applications hosted in AWS, AWS Cloud Administration, Terraform, Ansible, Amazon Machine Images (AMI), EC2 scripting, Lambda functions.
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Hands-on experience with any of the following data orchestration stack, ingestion frameworks, cloud-native patterns: Apache Airflow, Kafka, Nomad/Terraform, Kubernetes/Docker, etc. Hands on experience with open-source distributed SQL engines - like Presto, Apache Drill or Dremio and ingestion/processing stack like Hadoop, Spark and Kafka is a must.
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Deep understanding of Apache Spark, Delta Lake, and related big data technologies, and proficiency in modern programming languages such as Python and Scala. Experience with Spark jobs for data processing, analysis, and machine learning tasks using Databricks.
$95,900 - $129,400 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience in Big Data ecosystem : ETL, tooling of Big Data Platform (Apache Spark, Airflow), Datalake, Synapse or Snowflake. As a Senior Reliability Engineer, you will play a critical role in ensuring the robustness, availability, and performance of our cutting-edge Data Engineering and Machine Learning Platforms.
$82,000 - $185,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our main tech stack includes Snowflake, Apache Airflow, AWS cloud infrastructure (, Kinesis, Kubernetes/EKS, Lambda, Aurora RDS PostgreSQL), Python and Typescript. You’ll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Experience with Big Data platforms such as Databricks or Apache Spark. Experience with the Azure Ecosystem (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Machine Learning (AML), Azure Cognitive Services, Azure Storage.
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Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML. Design, build, test and maintain the Machine Learning platform supporting Data Science initiatives.
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Previous experience as a software engineer, applied mathematician, or in roles involving DevOps, MLOps, Databricks, and Apache Spark is highly regarded. - Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow.
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Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks. Proven experience as a Technical Lead with a focus on Databricks and big data technologies on Azure Cloud Platform.
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We use Apache Airflow, Python, and Apache Spark for ETL. For streaming data, we use Apache Kafka managed by a vendor and use Kafka Connect, Kafka Streams, and Spark Streaming for stream processing.
ExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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Senior Data Technical Lead (Life/Annuity exp, Databricks Expertise) Handson experience in writing python code, Pyspark notebooks and Azure Cloud, Configure Databricks clusters and ensure adherence to best practices and coding standards.
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