Job Description
Looking for a Data Architecture Strategy Lead who's genuinely interested in Data Engineering and wants to make an impact from day one.
You'll be working out of Bengaluru (hybrid), and honestly, the day-to-day is going to revolve around Model Evaluation & Tuning and Python. We're not looking for someone who just ticks boxes - we want someone who actually cares about data engineering.
On paper, we'd expect M.Sc (Data Science) and somewhere around 15 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 14.8-75.7 LPA - fair for the senior level band and open to discussion based on what you bring.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Learning and certification support is available for tools and frameworks directly relevant to the role. The next logical step from this position is a senior or lead-track role within the same function.
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. The package is structured with a fixed component, performance bonus, and standard health coverage.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
You'll be working out of Bengaluru (hybrid), and honestly, the day-to-day is going to revolve around Model Evaluation & Tuning and Python. We're not looking for someone who just ticks boxes - we want someone who actually cares about data engineering.
On paper, we'd expect M.Sc (Data Science) and somewhere around 15 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 14.8-75.7 LPA - fair for the senior level band and open to discussion based on what you bring.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Learning and certification support is available for tools and frameworks directly relevant to the role. The next logical step from this position is a senior or lead-track role within the same function.
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. The package is structured with a fixed component, performance bonus, and standard health coverage.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.