Case Studies

Mandates we have closed.

7 mandates from our talent acquisition work across India's financial services and fintech sector. Client names are withheld and figures are given as ranges to protect confidentiality. The placements, and the outcomes, are real.

40+
technology roles placed in FY26
90%+
offer-to-join
Zero
replacements to date
4-6
weeks, brief to offer
Wealth-Tech
Industry Series B wealth-tech platform
Mandate 4 Salesforce FSC engineers
Engagement Success-fee
Outcome All four placed; no replacements in eighteen months

Four Salesforce FSC engineers for a Series B wealth-tech in five weeks, none replaced at eighteen months

Starting point. Three agencies had already sent full-stack generalists, and two senior offers had collapsed at offer stage the previous quarter.

Brief to offer
Five weeks, brief to offer
Shortlist
Three to four per seat
Offer to join
Four of four joined
Replacement status
No replacements at eighteen months

Challenge

A Series B wealth-tech platform needed four Salesforce Financial Services Cloud engineers with real domain context in wealth management workflows. Three agencies had already been through the brief and sent full-stack generalists with no financial services awareness. Two senior candidates had collapsed at offer stage the previous quarter because they could not translate generic CRM experience into the regulatory workflow the platform actually ran on. The problem was not supply of Salesforce engineers. It was supply of Salesforce engineers who understood wealth.

Approach

We mapped the wealth management value chain end to end and screened against it: portfolio management systems, advisory workflows, the SEBI compliance touch points a wealth platform lives with. Every candidate was tested on two axes at once, technical depth in FSC architecture and integrations, and domain vocabulary. The screening question underneath all of it was simple. Could this person hold a twenty-minute conversation with the head of advisory operations without an interpreter?

Outcome

All four seats were filled within five weeks, each from a shortlist of three to four calibrated candidates rather than a long list padded to look like coverage. Eighteen months later, none of the four has been replaced, and the platform's head of engineering has said the screening calibration was the single largest reason the hires held. For a success-fee engagement, that retention is the whole point: the client paid once, not twice.

Wealth-Tech
Industry Wealth subsidiary of a major Indian financial group
Mandate DevOps Engineer, wealth platform infrastructure
Engagement Success-fee
Outcome Placed from a shortlist of three; still in role past its first year

A DevOps engineer for a regulated wealth platform in six weeks, from a shortlist of three, still in role after a year

Starting point. Earlier candidates from SaaS and consumer technology had cleared the technical screen and missed the regulated context.

Brief to offer
Four to six weeks, brief to offer
Shortlist
Three candidates
Offer to join
One of one joined
Replacement status
In role past the first year

Challenge

The wealth subsidiary of a major Indian financial group needed a DevOps engineer for its wealth platform infrastructure, and on paper it read like a standard DevOps search. It was not. The platform carries client portfolio data under SEBI custody and reporting obligations, runs in a compliance-constrained environment, and is operated by a team that needed someone comfortable with both the technical stack and the regulatory weight sitting on top of it. The candidates who had come through earlier, out of SaaS and consumer-tech backgrounds, kept missing that second half.

Approach

We screened for DevOps experience earned inside regulated financial services environments, not transplanted from consumer technology. The bar was infrastructure judgment in the specific context of a wealth platform: how client data is handled, whether a candidate's instinct on change management matched the discipline a regulated platform demands, whether they had lived the operational rhythms of a financial services technology team. We kept the list short on purpose.

Outcome

Three candidates went to the client, each one genuinely interviewable, and the offer closed within six weeks of the brief. More than a year later the engineer is still in the seat, and the change-management discipline the platform had been missing is now simply part of how the team operates. Because the first hire held, the subsidiary never paid the far larger cost of running the search a second time.

Captive Finance
Industry Captive finance arm of a global manufacturer
Mandate Senior delivery lead, customer acquisition applications
Engagement Success-fee
Outcome Senior hire earlier searches had missed; still leading the stack

A senior delivery lead for a captive finance arm in under two months, after two searches had failed

Starting point. Two prior searches had failed to land the role over the better part of a year.

Brief to offer
Six to eight weeks, brief to offer
Offer to join
One of one joined
Replacement status
Still leading the stack

Challenge

The captive finance arm of a global manufacturer needed a senior delivery leader for its customer acquisition applications, the stack that runs loan origination, onboarding, and the upstream systems feeding the captive's lending operations. The role sat on a fault line. It wanted the delivery discipline of senior engineering management and the operational instincts of someone who understood a captive attached to a manufacturing parent. Candidates who had one side of that profile but not the other had already been through the process without landing.

Approach

We concentrated the search on leaders who had delivered inside captive finance entities, or at NBFCs running acquisition stacks of comparable scale. Each was assessed against the real texture of a captive: accountability to a parent's commercial cycles, the integration seams between captive and parent systems, and the leadership style it takes to run delivery in that environment. Familiarity with customer-acquisition technology specifically was a prerequisite, not a nice-to-have.

Outcome

For a role that had defeated two earlier searches, the mandate closed inside the six-to-eight-week window we hold to for senior hires. The leader we placed is still running the acquisition applications stack, and the captive now has the delivery ownership it had been trying to buy for the better part of a year.

NBFC Lending
Industry Lending arm of a major Indian financial group
Mandate Data Engineer, lending portfolio analytics
Engagement Success-fee
Outcome Placed from a two-person finalist stage; held past six months

A lending data engineer for an NBFC in six weeks, from two finalists, held past six months

Starting point. Generalist candidates kept clearing the technical bar and failing the domain one.

Brief to offer
Four to six weeks, brief to offer
Shortlist
Two finalists
Offer to join
One of one joined
Replacement status
Held past six months

Challenge

The lending arm of a major Indian financial group needed a data engineer for its lending portfolio analytics. On the surface it was a generalist req, the same core stack and skills you would list for any data engineering role. Underneath, the lending context changed everything. The person had to understand retail-lending portfolio data structures, the regulatory reporting cadence lending analytics exists to serve, and the difference between building infrastructure for a credit risk function and building it for unregulated commercial analytics. Generalist candidates kept clearing the technical bar and failing the domain one.

Approach

We sourced from data engineers who had actually worked in lending, at banks, NBFCs, or fintech lenders, rather than dipping into the broad data engineering pool and hoping domain would follow. Generic fluency was the floor. What separated candidates was whether they understood lending portfolio data, regulatory reporting rhythms, and the day-to-day of supporting a credit risk and collections analytics function.

Outcome

The shortlist came down to two finalists, both of whom the client would have been comfortable hiring, and the offer closed inside six weeks. Past the six-month mark the engineer has settled cleanly into the lending analytics team, and the function now has data engineering that speaks the language of the portfolio rather than needing it explained.

Wealth-Tech
Industry Wealth-tech entity of a major Indian financial group
Mandate Salesforce Developer, wealth platform
Engagement Success-fee
Outcome Placed domain-ready, with no on-the-job ramp into wealth context

A Salesforce developer for a wealth platform in six weeks, productive from the first week

Starting point. Generalist Salesforce developers out of SaaS and consumer CRM work had been looked at before and had not converted.

Brief to offer
Four to six weeks, brief to offer
Offer to join
One of one joined

Challenge

The wealth-tech entity of a major Indian financial group needed a Salesforce developer for its wealth platform, and the requirement was specific in a way certifications do not capture: advisor productivity, portfolio management integrations, regulatory data handling, and the wider Financial Services Cloud ecosystem. Generalist Salesforce developers out of SaaS and consumer-tech CRM work had been looked at before and had not converted, because wealth-platform vocabulary and workflow simply do not transfer from generic Salesforce work.

Approach

We sourced from Salesforce developers who had built inside wealth, asset management, or the broader financial services world, and we screened for domain fluency in conversation rather than reading it off a stack of certifications. The question was never how many Salesforce badges a candidate held. It was whether they could sit with the wealth platform team and understand what the platform was for.

Outcome

The offer closed within the four-to-six-week window, and the developer arrived able to work wealth-platform context from the first week rather than spending a quarter learning it on the job. That saved ramp is the real return here: the team added capacity immediately instead of absorbing the drag of teaching domain to a strong generalist.

Wealth-Tech
Industry Wealth-tech entity of a major Indian financial group
Mandate Production Support specialist, wealth platform
Engagement Success-fee
Outcome Hired on operational fit over credentials; settled through the first quarter

A production support specialist for a wealth platform in five weeks, settled inside a quarter

Starting point. In earlier attempts, candidates with stronger development CVs had done worse than those with operational instincts.

Brief to offer
Three to five weeks, brief to offer
Offer to join
One of one joined
Replacement status
Settled through the first quarter

Challenge

The wealth-tech entity of a major Indian financial group needed a production support specialist for its wealth platform, the person who keeps it running for advisors and clients through business hours, owns incident response, and coordinates with engineering when something breaks. On a wealth platform, downtime during market hours costs money and trust, so the role wanted uptime discipline and the composure that comes with supporting a regulated financial services platform under pressure. In earlier attempts, candidates with stronger development CVs had actually done worse than those with proven operational instincts.

Approach

We screened for production support and operational engineering built in financial services or comparably regulated environments. The evaluation was about judgment under load: incident response, escalation, and the ability to talk to both engineers and business stakeholders while an issue is live. We deliberately de-prioritised headline development credentials in favour of operational fit, because that was what the role actually needed.

Outcome

The mandate closed in three to five weeks, and through its first quarter the specialist has settled into the production floor and the incident rhythm the platform runs on. The client got the outcome that matters for this role, someone who keeps the platform steady during market hours, rather than the most decorated CV in the pile.

Financial Services
Industry Financial services arm of a major Indian financial group
Mandate Data Engineer, financial services data platform
Engagement Success-fee
Outcome Second placement in the same group; closed faster on prior calibration

A second data engineer for the same financial group in under five weeks, because the first placement held

Starting point. The group came back because the first data engineering placement had held; the brief started from a known bar.

Brief to offer
Under five weeks, brief to offer
Offer to join
One of one joined
Replacement status
Second placement in the same group

Challenge

The financial services arm of a major Indian financial group needed a data engineer for its data platform, a parallel to a mandate we had already closed for the group's lending entity but with its own requirements: financial services data structures, regulatory reporting, and analytics for a broader business than pure lending. The client came back to us specifically because the first placement had held, which is its own kind of brief.

Approach

We ran the same domain-first screen that had worked on the group's lending mandate, sourcing from financial services data engineers and evaluating for real financial services data context rather than generic fluency. The advantage the second time was calibration. We already knew what this group considered a strong hire, which sharpened both the brief and the shortlist and took time out of the search.

Outcome

The offer closed in under five weeks, faster than the first mandate, precisely because the earlier placement had taught us the group's bar. It was the second specialist data engineering hire we had closed across the group's entities, and it turned a one-off search into the start of a repeat relationship, which for a specialist practice is worth more than any single fee.

Client names withheld at client request. Figures are stated as ranges to preserve confidentiality; exact numbers and references are available on engagement. Where a figure is not shown, the engagement record does not support stating it.

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