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Capgemini has open jobs for data engineers. They want recent grads or anyone with a degree. You don’t need experience. They are holding interviews off campus. Here’s what you need to know about the openings:
Job Description :-
| Company Name | Capgemini |
| Job Role | Data Engineer |
| Qualification | Any Graduates |
| Experience | 0 – 2 Years |
| Batch | Any Batch |
| Location | Bangalore, India. |
| CTC/Salary | Not Disclosed |
Tips to Prepare an ATS-Friendly Resume :-
1. Use Job Titles and Words the Posting Uses Match the words: Use the same skills, titles, and stuff they list in the job ad. These show you fit what they’re looking for. Avoid company lingo: Stick to words everybody uses over weird company talk.
2. Pick a Clean, Simple Setup Nix photos and graphics: Computer systems get confused by extra stuff. Keep it to plain text. Standard fonts: Use normal fonts like Arial or Times New Roman. Nice and simple. Clear sections: Use sections like “Experience” and “Skills” so it’s organized.
3. Make it Logical Organize it: List your jobs backwards with the newest first. Label sections clearly. Bullet points: Use bullet points to break up blocks of words and make it easy to scan.
4. What to Include Contact: Your name, phone/email, LinkedIn if you have one. Experience and abilities: Show professional experience and anything useful you can do, with numbers when possible (grew sales 20%). Education and certificates: Related degrees, training certificates, etc.
5. Use Keywords Skills/strengths: Both technical skills and soft stuff like communication or leadership. Job titles: Use the same words for roles that everyone does. Action verbs: Use strong verbs like “managed” “created” “led” to show what you achieved.
6. Format: Word (docx) or PDF File type: docx or PDF both work for systems. But double check what they want posted, PDFs can get weird sometimes.
7. Test it Out ATS test sites: Copy/paste your resume into sites that test how the system will read it to catch issues. Plain text check: Paste into plain text doc to see how it looks without formatting.
8. Check for Mistakes Spelling/grammar: Make sure no typos or grammar problems. Looks bad and can mess up reading!
Tips for acing the job interview:-
Beforehand
– Learn about the company. Understand what they do, what they care about, all that. See what skills and stuff are needed for the actual job.
– Practice answering common questions like tell me about yourself and what are your strengths and weaknesses? Have real-life stories ready to go.
– Prepare some good questions to ask about the job, the team, training programs
– it shows you really want it.
– Have your elevator pitch down. A short spiel about your background and what you bring to the table.
– Dress to impress, even if the office is casual. Better overdressed than under.
During the Big Day
– Get there 10-15 minutes early in case anything makes you late. They notice punctuality.
– Smile, eye contact, solid handshake. Sit with good posture and lean in to show you’re engaged.
– Listen close to each question asked. Take a sec before answering if you need it. Don’t ramble, get to the point.
– Be cool answering tricky questions too. Stay calm, be honest if you’re unsure, and say how you’d figure it out.
Afterwards
– Send a thank you email expressing continued interest in the gig. Do this within 24 hours.
– Review how it went. What answers flowed well or needed polish? File it away for next time.
– Don’t bug them too much while they make a decision. If it’s been as long as they said the process takes, politely check in.
Eligibility / Qualification:-
- A ton of experience with Python and popular libraries like TensorFlow or scikit-learn that are used for machine learning
- Know your way around stuff like clustering (putting similar data points together) and classification (like recognizing images)
- Good understanding of natural language processing and recommendation systems
- Know databases well, both normal ones like MySQL and less structured ones
- Can design databases and make queries run faster to get data quicker
- Strong grip of areas like object oriented programming, threads, processes, memory
- Know how to check if machine learning models are working right
- Have put models to work in real systems before
- Currently on an Agile team using version control like Git
Responsibilities:-
- Get raw data and organize it
- Build systems to move and store data
- Figure out what the business wants and needs
- Spot patterns and trends in data
- Do analysis on complex data and report back
- Prep data so it can be used for predictive modeling
- Build algorithms and prototypes
- Combine data from different places
- Find ways to make data better
- Spot new sources of data
- Create analytical tools and programs
- Work with data scientists and architects on projects
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