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Our stack includes Kubernetes, Docker, GCP, AWS, Azure, Ansible, Terraform, Vault, Backstage, Gitlab, Tensorflow, Datadog, Elasticsearch, Kafka, Hadoop, MySQL, MongoDB, Python, and Go. Proficiency with programming languages like Python, Golang, and shell scripting to automate tasks.
$140,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experiencewithmodern data technologies/stack such as cloud services (AWS, Azure, GCP), Containerization (Docker, Kubernetes), Databases (Redshift, Snowflake), Programing languages (R, Python, SAS), VCS and CICD (GitHub, GitLab, CodeCommit, Jenkins, CodePipeline.
$165,200 - $236,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Scripting experience including at least a subset of the following: Bash, Python, Zsh, AppleScript, Terraform, Ansible, Puppet, Chef. Experience developing and maintaining CI/CD pipelines on cloud platforms including AWS, Azure, or GCP.
$120,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Data science tools/languages: R, R Studio, Python (data preparation and analysis libraries), Databricks, etc. AWS cloud services such as EC2, EMR, RDS, Redshift, Glue, SageMaker (or Azure and GCP equivalents.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Experience with cloud data platforms (e.g., AWS, GCP, Azure) and a deep understanding of data security and quality governance. Strong understanding of SQL and programming languages (Python, Java, Scala) with a solid foundation in machine learning algorithms and other data science fundamentals.
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Work closely with Tech Anchor, Product Manager and Product Owner to deliver MLOPs platform and Gen AI solution in GCP using Python and other tools for the data scientists and business across the company.
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GCP - Artifact Registry, Container Registry, Cloud Composer, Cloud Functions, Cloud Run, Data Proc, Languages - Python, SQL, MQL, Docker. Productivity - G-Suite, Lucid Chart, Jira, Confluence, Slack.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Js, PostgreSQL / Amazon Aurora, Python, Airflow, Docker, Kubernetes, Redis, Snowflake, Confluent, Cognito, Cloudfront, S3, API Gateway, Lambda, Amazon Serverless Architecture. Experience with cloud technologies, e.g., AWS, Azure, GCP, Docker, or Kubernetes.
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Implementing processes for meeting IAM controls including periodic reporting capabilities on access, reconciliation between SailPoint and Azzure and GCP tenants. We will also at some point of time build in GCP. Having experience in IAM for Azure, AWS and GCP is preferred.
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Experience with Google Cloud Platform (GCP) using tools like BigQuery, Cloud Composer, Dataproc and Dataflow. Experience on Big Data technologies like Hadoop, Spark, any cloud platform like GCP, Azure, AWS, Snowflake.
$61,800 - $123,600 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Good understanding of data pipeline design concepts, Hands-on experience with Postgres and Snowflake, Excellent coding skills in Python, Experience with Apache Airflow and Apache Spark tools, Knowledge of AWS, Experience with CI/CD tools and processes, Good communication skills.
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Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
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Experience with cloud services, preferably GCP Services like Vertex AI, Cloud Function, BigQuery etc. Experience working with Google Cloud platform(GCP) – specifically Google Kubernetes engine, Terraform, and infrastructure.
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Deep understanding of AWS/GCP/OCI cloud services and how to leverage them for compute, storage, and managed services including, but not limited to databases, managed Kubernetes, and Python/Django application services.
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