Apply for Atlassians Off Campus Drive 2025! Hiring Data Engineer Job in Bangalore or remotely as a Data Engineer (2-5 years). Build scalable data pipelines, work with big data. Competitive salary for BE/BTech graduates passionate about data lakes.
Candidates who are interested in Atlassians Off Campus Drive Job Openings can go through the below to get more information.
Key Job details of Data Engineer jobs
Company: Atlassians
Qualifications: BE/BTech
Experience Needed: 2-5 years
Job Description
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Atlassian is looking for a Data Engineer to join our Data Engineering team, responsible for building our data lake, maintaining big data pipelines / services and facilitating the movement of billions of messages each day. We work directly with the business stakeholders, platform and engineering teams to enable growth and retention strategies at Atlassian. We are looking for an open-minded, structured thinker who is passionate about building services/pipelines that scale.
On a typical day you will help our stakeholder teams ingest data faster into our data lake, you’ll find ways to make our data pipelines more efficient, or even come up ideas to help instigate self-serve data engineering within the company. You will be involved in strategizing measurement, collecting data, and generating insights.
Apply Now for Atlassians Data Engineer Jobs
How to Apply Atlassians Off Campus Drive 2025
Click on Apply to Official Link Atlassians Above – You will go to the Company Official site
First of all Check, Experience Needed, Description and Skills Required Carefully.
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Interview Questions
- Can you describe your experience building and optimizing big data pipelines?
- How do you ensure scalability and efficiency in a data lake environment?
- What is your approach to writing performant SQL queries for large datasets?
- Can you share an example of a data engineering solution you implemented?
- How do you collaborate with stakeholders to define data requirements?
- What experience do you have with cloud platforms like AWS or Databricks?
- How do you handle debugging issues in data pipelines or services?
- Can you explain a time you enabled self-serve data engineering for a team?
- What strategies do you use to stay updated with big data technologies?
- How do you balance business needs with technical constraints in data projects?
