Case Studies

Mandates we have closed.

Seven case studies from our talent acquisition work in India's financial services and fintech sector. Client names are not disclosed. The placements and outcomes are real.

Wealth-Tech
Industry Series B wealth-tech platform
Mandate 4 Salesforce FSC engineers
Outcome All 4 placed. Zero replacements at 18 months.
Engagement Success-fee

Closing a niche FSC mandate three prior agencies could not crack

Challenge

A Series B wealth-tech platform needed four Salesforce Financial Services Cloud engineers with deep domain context in wealth management workflows. Three previous agencies had submitted full-stack generalists with no financial services awareness. Two senior hires had fallen through at offer stage in the previous quarter because the candidates could not translate their generic CRM experience to the regulatory workflow the platform needed.

Approach

We mapped the wealth management value chain end to end and screened candidates specifically for experience with portfolio management systems, advisory workflows, and SEBI compliance touch points. Each candidate was evaluated on both technical depth (FSC architecture, integrations, custom Lightning components) and domain vocabulary. Could they hold a 20-minute conversation with the head of advisory operations.

Outcome

All four positions filled within five weeks. Each shortlist averaged three to four candidates per role. Zero replacements invoked at 18 months. The platform's head of engineering wrote later that the screening calibration was the single largest factor in retention.

Wealth-Tech
Industry Wealth subsidiary of a major Indian financial services group
Mandate DevOps Engineer, wealth platform infrastructure
Outcome Placement landed and held in role
Engagement Success-fee

A DevOps hire where infrastructure judgment mattered more than tooling fluency

Challenge

The wealth subsidiary of a major Indian financial services group needed a DevOps Engineer for its wealth platform infrastructure, but the role required more than standard DevOps tooling fluency. The platform handles client portfolio data subject to SEBI custody and reporting requirements, runs in a compliance-constrained environment, and is operated by a team that needed someone who could navigate both the technical platform and the regulatory awareness that comes with wealth management infrastructure. Previous candidates from generalist DevOps backgrounds had not understood the difference.

Approach

We screened specifically for DevOps experience in regulated financial services environments rather than in SaaS or consumer technology contexts. Each candidate was evaluated on infrastructure judgment in the specific context of wealth platform operations: handling of client data, change management discipline appropriate for a regulated platform, and familiarity with the operational rhythms of a financial services technology team. The shortlist was tight rather than broad.

Outcome

The placement was made and the candidate joined the wealth platform team. The platform's engineering function gained the specialist DevOps capability it had been seeking through earlier unsuccessful searches.

Captive Finance
Industry Captive financial services arm of a major global manufacturer
Mandate Senior delivery role, customer acquisition applications
Outcome Placement landed and held in role
Engagement Success-fee

A senior captive finance hire requiring both domain depth and platform delivery leadership

Challenge

The captive financial services arm of a major global manufacturer needed a senior delivery leader for its customer acquisition applications: the technology stack that handles loan origination, customer onboarding, and the upstream applications that feed the captive's lending operations. The role required someone who understood both the platform delivery discipline of senior engineering management and the specific operational context of a captive finance entity attached to a manufacturing parent. Candidates with either side of the experience profile but not both had not landed in earlier searches.

Approach

We focused the search on candidates with proven delivery leadership at captive finance entities or at NBFCs with comparable acquisition stack scale. Each candidate was evaluated on their ability to operate within the specific dynamics of a captive: accountability to a manufacturing parent's commercial cycles, the integration requirements between captive and parent systems, and the leadership style required to run a delivery team in this environment. Domain familiarity with customer acquisition technology specifically was a screening prerequisite.

Outcome

The placement was made and the candidate joined the captive finance team. The acquisition apps function gained the senior delivery leadership it had been searching for.

NBFC Lending
Industry Lending arm of a major Indian financial services group
Mandate Data Engineer, lending portfolio analytics
Outcome Placement landed and held in role
Engagement Success-fee

A Data Engineer hire where lending domain context filtered the shortlist sharply

Challenge

The lending arm of a major Indian financial services group needed a Data Engineer for its lending portfolio analytics function. The role looked superficially like a generalist data engineering hire: same core stack, similar skill requirements on paper. But the lending context made it materially different. Candidates needed to understand the data structures specific to retail lending portfolios, the regulatory reporting cadence that lending data engineering serves, and the difference between building analytics infrastructure for a credit risk function versus building it for an unregulated commercial analytics use case. Generalist data engineering candidates without lending domain context had not converted in earlier searches.

Approach

We screened specifically for data engineering experience in lending environments: banks, NBFCs, or fintech lenders, rather than from broader data engineering pools. Each candidate was evaluated for understanding of lending portfolio data structures, regulatory reporting requirements, and the operational dynamics of supporting a credit risk and collections analytics function. Generic data engineering fluency was a baseline, not a differentiator.

Outcome

The placement was made and the candidate joined the lending analytics team. The function gained specialist data engineering capability aligned with the regulatory and operational context of lending analytics.

Wealth-Tech
Industry Wealth-tech entity of a major Indian financial services group
Mandate Salesforce Developer, wealth platform
Outcome Placement landed and held in role
Engagement Success-fee

A Salesforce Developer who understood wealth platform context, not just Salesforce tooling

Challenge

The wealth-tech entity of a major Indian financial services group needed a Salesforce Developer for its wealth platform. The role required specialist familiarity with Salesforce in the context of wealth management workflows: advisor productivity, portfolio management integrations, regulatory data handling, and the broader Salesforce Financial Services Cloud ecosystem. Generalist Salesforce developers with CRM-focused backgrounds at SaaS or consumer technology firms had been considered in earlier searches but had not converted, because the wealth platform context required vocabulary and workflow understanding that does not transfer from generic Salesforce work.

Approach

We sourced specifically from Salesforce developer pools with prior wealth management, asset management, or broader financial services Salesforce experience. Each candidate was evaluated on the specifics of wealth platform Salesforce work, not on Salesforce certifications or generic CRM development experience. Domain vocabulary fluency was screened in conversation, not assumed from a CV.

Outcome

The placement was made and the candidate joined the wealth platform team. The Salesforce developer function gained capability aligned with wealth platform context rather than requiring on-the-job domain ramp.

Wealth-Tech
Industry Wealth-tech entity of a major Indian financial services group
Mandate Production Support specialist, wealth platform
Outcome Placement landed and held in role
Engagement Success-fee

A Production Support hire where uptime discipline mattered more than headline credentials

Challenge

The wealth-tech entity of a major Indian financial services group needed a Production Support specialist for its wealth platform: the function that keeps the platform operational for advisors and end clients during business hours, manages incident response, and coordinates with the engineering team on production issues. The role required someone who understood the specific uptime expectations of a wealth platform, where downtime during market hours has commercial and client-trust consequences, and the operational discipline that comes with production support in a regulated financial services environment. Candidates with stronger headline engineering credentials had been less successful than those with proven production discipline in regulated environments.

Approach

We screened for production support and operational engineering experience at financial services or regulated industry platforms specifically. Each candidate was evaluated on operational judgment: incident response discipline, escalation handling, communication with both technical and business stakeholders during production events, and familiarity with the rhythm of supporting a financial services platform during active business hours. Headline development credentials were de-prioritised in favour of operational fit.

Outcome

The placement was made and the candidate joined the wealth platform production support function.

Financial Services
Industry Financial services arm of a major Indian financial services group
Mandate Data Engineer, financial services data platform
Outcome Placement landed and held in role
Engagement Success-fee

A second specialist data engineering placement within the same financial services group

Challenge

The financial services arm of a major Indian financial services group needed a Data Engineer for its data platform: a parallel mandate to one PeopleCap had previously closed for the group's lending entity, but with distinct requirements specific to the financial services arm's business model. The data engineering profile required familiarity with financial services data structures, regulatory reporting requirements, and the operational dynamics of supporting analytics for a broader financial services business beyond pure lending.

Approach

We applied the same domain-focused screening approach proven on the earlier data engineering placement for the group's lending entity: sourcing from financial services data engineering pools specifically, evaluating for financial services data context rather than generic data engineering fluency. The previous placement provided useful calibration for what the group considered a strong fit, which sharpened the brief and shortlist for this mandate.

Outcome

The placement was made and the candidate joined the financial services data team. The mandate marked the second specialist data engineering placement PeopleCap had closed within the group across separate entities.

Client names withheld at client request. References available on engagement.

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