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Accenture is looking to hire grads for Infor as data engineers. No experience needed. They want students and recent grads of any major. Even if you didn’t study computer science or IT, don’t worry. They’ll train you onsite. It’s an off-campus hiring event. So you won’t need to formally apply online or anything. Just show up and they’ll interview people there.
Job Description :-
| Company Name | HSBC |
| Job Role | Data Engineer |
| Qualification | BE Bachelor of Engineering |
| Experience | Fresher/ Experienced |
| Batch | Any Batch |
| Location | Bengaluru, India |
| CTC/Salary | Not Disclosed |
Tips to Prepare an ATS-Friendly Resume :-
1. Use Keywords from the Job Description – Read the job post carefully and make a list of key tech terms and skills they mention – Python, SQL, stuff like that. – Work those words into your resume, especially in the skills section, the intro, and when you describe your experience.
2. Keep It Simple – Use standard sections like Work Experience, Skills, Education. – Avoid fancy formatting with graphics and charts and weird fonts – that’ll just confuse the computer. Keep it clean and basic.
3. Structure It Well – Put your contact info at the top – name, phone, email, LinkedIn if you have it. – Summarize your experience and achievements in data engineering at the top – be brief but make it attention-grabbing. Tailor it to each job you apply for. – List your tech skills – SQL, Python, etc. Also soft skills like problem-solving and communication. – Describe work you’ve done that’s relevant to data engineering. Use bullet points to show achievements. Use numbers to show impact, like “improved processing speed by 25%”.
4. Use Action Words and Numbers – Start bullet points with power words like “Designed,” “Developed,” “Optimized”. – Use numbers to quantify achievements whenever possible. Like “Reduced processing time 30% by optimizing data pipelines”.
5. Customize For Each Job – Tweak your resume to highlight the stuff in your background that best fits each job.
6. List Relevant Projects – Describe data engineering projects you’ve worked on – tech used, your role, etc. Pick ones that align closely with the job requirements.
Tips for acing the Data Engineer job interview:-
Dos
1. Brush Up on Key Concepts Know Core Ideas: Review main data engineering things like ETL, warehouses, data models, database optimization. Learn Tools: Know tools and tech used a lot in data engineering like Hadoop, Spark, SQL, AWS and Azure.
2. Practice Coding and SQL Coding Tests: Do coding to manipulate data, algorithms, data processing. Use LeetCode, HackerRank. SQL Skills: Be ready to write and make SQL queries run faster. Show joins, aggregations, subqueries.
3. Show Problem-Solving Chops Explain Approach: When they give you a problem or case, walk through how you’d tackle it – assumptions, steps. Share Examples: Talk about actual times you solved similar stuff and what happened after.
4. Show You Get Data Pipelines Design Pipelines: Chat how to build data pipelines – handle quality, scale, speed. Get Architectures: Know batch vs stream processing tradeoffs and how to work with them.
5. Communicate Well Clear Explanations: Practice explaining complex tech things clearly and concisely. Listen Up: Listen close to questions and respond thoughtfully. Ask more if you need.
6. Prep for Behavior Questions Use STAR: Structure answers with Situation, Task, Action, Result to show experience.
7. Ask Good Questions Company Stuff: Ask about their data, tools, upcoming projects or issues. Team Details: Inquire about team structure, your role’s impact, integration.
Don’ts
1. Don’t Forget Basics Core Knowledge: Know fundamental data engineering cold.
2. Don’t Complexify Answers Keep Simple: Don’t overcomplicate stuff. Be clear and concise.
3. Don’t Bad-mouth Stay Positive: Don’t bad-mouth past jobs. Focus on lessons learned.
4. Don’t Speed Talk Take Time: Think through technical/problem-solving responses. Vague is bad.
5. Don’t Overlook Soft Skills Balance Is Key: Tech is vital but don’t underestimate communication/teamwork.
6. Don’t Skip Prep Research Company: Learn their tech and data difficulties beforehand. Tailor Answers: Respond directly to the role’s needs.
Eligibility / Qualification:-
- – You’ve worked with data before as an engineer or something similar
- – You know your stuff when it comes to data models, pulling data, and grouping it
- – You can code in Python, Java or other languages
- – You have real experience with structuring SQL databases
- – You’re great with numbers and analysis
- – You have a university degree in a field like Computer Science or IT
- – bonus points if you have a Master’s!
- – Extra credit if you have a data engineering certificate from someone like IBM
Roles and Responsibilities:-
- – Look at raw data and organize it – Build systems to store and move data around – Understand what the business needs and wants to do – See trends and patterns in the data – Do complex analysis of the data and share what we learn – Get data ready so we can predict stuff – Build little test programs and ideas – Mix together raw data from different places – Find ways to make the data better – Figure out how to get more data – Create tools to analyze the data – Work with data scientists and architects on projects
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