| Lead Data Engineer with GCP || Remote || 12+ Years || GC/ USC at Remote, Remote, USA |
| Email: [email protected] |
| Hi All, Lead Data Engineer with GCP Remote 12+ Years Visa: GC/ USC JD: - Need to be experienced as a lead (example he gave was 10 years as a data engineer/few years as a lead. - Databricks, python: MUSTS, he listed GCP as a strong nice to have, but I really believe they will go with a candidate that is strong with GCP Specific technical skills: - - extensive knowledge of data principals, patterns, processes and practices - - Databricks - - SQL - - Python - - GCP - understanding (especially dataflow, pub/sub, composer) Timeline/process: - Submittals need to have Dave Nelson/Amy Jackson ccd - Dave will review resumes and prescreen candidates. He will then provide feedback on who will go external (we will be sending 2 for each role). - The candidates going external will complete the hirevue and Dave will also provide us with the sizzle specific to each candidate. Additional details on the project below: This team is on the front end of their journey- working through the analytics now understanding problems reporting identify/change/create policies evaluate performance/mitigate issues be able to operate in real time based on the data Team will be part of the E2E Fresh domain. E2E Fresh is responsible for perishable products like produce, meat, seafood and dairy. Specifically, this team will be responsible for data related to refrigerated supply chain, or Cold Chain as we call it. Cold Chain data includes data from temperature sensors, purchase orders, warehousing, and transportation routing and location. The overall goal is to use this data increase freshness of food at the stores. Job Details: working with ingestion pipelines for data from internal and external applications. curation and presentation of application data to internal consumers. Join data from multiple systems to create Fresh Domain Data Investigate and mitigate data quality issues. The journey of data enabling E2E Fresh will usually follow a path of Analytics to discover improvement opportunities, Reporting to allow operations to target improvement, and Event (real-time) Data to participate in operations. A hypothetical example would be: Analytics reveals that strawberries are frequently subjected to high temperatures in transit from distribution center to stores. Management knows they have a problem and assigns operations to investigate. Reports are given to operations managers to help them investigate and try an operational change like a temp check when the truck leaves the yard. Reports allow them to monitor and evaluate the effectiveness of the change on strawberry freshness. The changes might mitigate some instances but not all. Transportation and/or stores are given real time data. This will allow them to be alerted that a truck is en route to the store with a high temperature. They turn the truck around before it even hits the store's loading dock and a replacement order is processed. This saves employee time and speeds up the replenishment process, resulting in fresher strawberries in the store. Thanks & Regards Mohd Faisal [email protected] www.signinsol.com To follow and receive more updates please Click Here -- Keywords: information technology golang green card Maryland Lead Data Engineer with GCP || Remote || 12+ Years || GC/ USC [email protected] |
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| Wed Jul 17 01:03:00 UTC 2024 |