#JeRecrute un ou une #dataengineer pour le datalab de #VIGINUM, le service en charge de la lutte contre les ingérences numériques étrangères en France.

N'hésitez pas à postuler.

https://www.welcometothejungle.com/fr/companies/viginum/jobs/ingenieur-data-viginum-h-f_paris

#dataeng #pythonjob #disinfo #fimi

Hey all, I'm hiring for a #DataEng (and #DevOps) role in the SF Bay Area. Reach out directly to me for more info.

#Java background is a strong want plus AWS and a desire to work on #OpenSource stuff.

Arkflow: A new Rust stream processor that combines performance with simplicity. Data pipelines just got better.

#rust #streaming #dataeng https://github.com/chenquan/arkflow

Do you know of any #rstats teams who could use some help in 2025?

I'm a freelance consultant with 10yrs of experience in #DataSci, #DataEng, #DataOps, and providing #SysAdmin for related tools. I primarily work with R, but I have enough SQL and Python knowledge to get by. I know my way around a linux terminal and docker-compose file. I'm also handy as an interpreter between IT and analytics teams. Open to many types of engagements (project-based, temp staff, etc).

If you have a need or a lead, I'd love to chat!

boosts welcome :-)

⁉️ Trying to develop your eng skills or pivot to #mleng or #dataeng and don't have prior CS experience?

➡️ The Missing README by Chris Riccomini, Dmitriy Ryaboy ( https://read.amazon.com/kp/embed?asin=B08XM2CDZM&preview=newtab&linkCode=kpe&ref_=cm_sw_r_kb_dp_4AEZSC0KTN6PYCEVA7KF&utm_content=bufferbec7b&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer )

➡️ The Coding Career Handbook by Swyx (https://learninpublic.org/?utm_content=buffer9108b&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer )

➡️ How Computers Really Work by Matthew Justice ( https://www.amazon.com/Amps-Apps-How-Computers-Work/dp/1718500661/ref=sr_1_3?crid=3O6LN6GLFSH23&dchild=1&keywords=how+computer's+really+work&qid=1635179511&sprefix=how+computer's+really+wor,aps,150&sr=8-3&utm_content=buffer60283&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer )

➡️ MIT's Missing CS Semester: https://missing.csail.mit.edu/?utm_content=bufferdee25&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

➡️ Beyond the Basic Stuff with Python by Al Sweigart ( https://www.amazon.com/Python-Beyond-Basics-Al-Sweigart/dp/1593279663/ref=sr_1_1?dchild=1&keywords=beyond+the+basic+stuff+with+python&qid=1635179598&sprefix=beyond+the+basic+stuff+with+pyth,aps,137&sr=8-1&utm_content=buffercfe07&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer )

Here's another nice one pointing out that one reason we need so many/much data eng is that we have frustrating tools and systems. And that managed services will abstract that away. DE will then be for customization, which is what it should be: solve the thorny, not the boring.

How soon? Well, that's always the question... but not soon enough is my snarky response. Also, "not invented here" and cost stops adoption of some usefuls.

https://rdrn.dev/data-engineering/

#data #datascience #dataeng