Job Description
Data Engineering Analyst | Kolkata | INR 6.2-11.8 LPA
Data Engineering role, junior level, full-time.
Need: B.Tech/B.E (CS/IT), 1+ yrs.
Core skills: Data Engineering, Java/Python/JavaScript, Agile/Scrum, Object-Oriented Design.
If this fits your profile in data engineering, apply now.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Learning and certification support is available for tools and frameworks directly relevant to the role. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The package is structured with a fixed component, performance bonus, and standard health coverage.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Interested candidates should be prepared to walk through relevant past work during the interview process. References may be requested closer to the offer stage rather than at the start of the process.
The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The organisation has historically promoted from within for a majority of its senior and lead openings. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Data Engineering role, junior level, full-time.
Need: B.Tech/B.E (CS/IT), 1+ yrs.
Core skills: Data Engineering, Java/Python/JavaScript, Agile/Scrum, Object-Oriented Design.
If this fits your profile in data engineering, apply now.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Learning and certification support is available for tools and frameworks directly relevant to the role. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The package is structured with a fixed component, performance bonus, and standard health coverage.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Interested candidates should be prepared to walk through relevant past work during the interview process. References may be requested closer to the offer stage rather than at the start of the process.
The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The organisation has historically promoted from within for a majority of its senior and lead openings. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.