| Data engineer with Databricks, MLOps, Spark and AWS::Beaverton, Oregan or Pleasanton, CA, Hybrid::4+ months-NO H1 at Beaverton, Oregon, USA |
| Email: [email protected] |
| From: AMIT, SUS [email protected] Reply to: [email protected] Position: Data engineer with Databricks, MLOps, Spark and AWS Location: Beaverton, Oregan or Pleasanton, CA, Hybrid Duration: 4+ months Phone and Skype Must have: We are not looking for ML engineers or Data Scientist, we are looking for Software engineers, candidates from data side with ML Ops Must have- Data Bricks, AWS, Spark, ML Ops, need independent consultants , data pipeline with ML. ETL pipeline. someone who has done migration type projects will be the best fit. Whats your opinion on Data bricks vs AWS pros and cons About The Team Data pipeline and ETL tooling are some of the most important components required to make ML successful. Unification of these tools enables us to simplify our development and invest all effort and enhancements into a single platform. Our ML tooling must enable ML applications to be easily built, maintained, deployed and validated. By platformizing our ML pipeline tools, Workday can build many high value ML solutions very quickly. Today, ML productivity can play a huge role in product success - this investment into improving data pipeline and ETL tooling is exactly what our team does. We strive to provide industry-leading solutions to ML and data engineering problems for Workday developers and Workday customers. We are made up of an eclectic group of dedicated individuals who pull experience from almost every corner of Workday and some of todays top tech companies. We take great pride in being relentlessly innovative, intensely encouraging, and persistently positive. For Junior Candidate: 2 roles open As a Software Development Engineer in ML, you will: Transition Databricks pipelines to Workday Data Engineering tooling on AWS Transition Databricks notebooks to AWS SageMaker Studio Develop features for Workday Data Engineering tooling that promote data mesh architecture principles Lead teams through best practices in ML and ML Ops Influence the direction of our product vision and strategy with technical expertise and context Provide critical feedback for the teams technical designs, architecture, and decisions Basic Qualifications: 1 or more years of experience using Databricks 1 or more years of experience using ML pipeline tools: Airflow, Dagster, ML Flow, AWS Glue, Spark, etc. 2 or more years of experience using cloud compute technologies: AWS, GCP, etc. 3 or more years of experience building production grade software and practicing Agile methodologies Other Qualifications: 2 or more years of experience building data mesh architectures 2 or more years of experience with ML ops 2 or more years of experience with machine learning and data science technologies As a Software Development Engineer in ML, you will: Transition Databricks pipelines to Workday Data Engineering tooling on AWS Transition Databricks notebooks to AWS SageMaker Studio Develop features for Workday Data Engineering tooling that promote data mesh architecture principles Lead teams through best practices in ML and ML Ops Influence the direction of our product vision and strategy with technical expertise and context Provide critical feedback for the teams technical designs, architecture, and decisions About You Basic Qualifications: 2 or more years of experience using Databricks 2 or more years of experience using ML pipeline tools: Airflow, Dagster, ML Flow, AWS Glue, Spark, etc. 2 or more years of experience using cloud compute technologies: AWS, GCP, etc. 5 or more years of experience building production grade software and practicing Agile methodologies Other Qualifications: 3 or more years of experience building data mesh architectures 3 or more years of experience with ML ops 3 or more years of experience with machine learning and data science technologies Regards, Amit Panthri Sr. Technical Recruiter E: [email protected] Keywords: machine learning California Data engineer with Databricks, MLOps, Spark and AWS::Beaverton, Oregan or Pleasanton, CA, Hybrid::4+ months-NO H1 [email protected] |
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| Wed May 29 00:31:00 UTC 2024 |