Business Analyst

Finkraft

Bengaluru

On-site

INR 2,400,000 - 3,600,000

Full time

19 hours ago

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Job summary

Finkraft is seeking a Senior Business Analyst — Data & Client Intelligence to lead AI-augmented analytics for enterprise clients in Bengaluru. You will own AI-driven analysis pipelines, manage data BA teams, and drive automation BRDs and dashboards with SQL and BI tools.

You will build AI-powered workflows, surface insights from client data, and ensure high-quality outputs for QBRs, RCA, BRDs, and dashboards.

Qualifications

6+ years in business analysis, data analytics, or consulting in B2B SaaS, fintech, or enterprise services.
SQL at an advanced level: complex joins, window functions, aggregations.
Tableau or Power BI: has built dashboards from scratch.
AI tools in daily workflow today: ChatGPT, Claude, Cursor, or equivalent.
Has managed a team of analysts or BAs: performance conversations and output standards.
Has presented data-backed analysis to CFOs or senior stakeholders.
Has written BRDs or FRDs that engineering shipped without PM translation.

Responsibilities

Default to AI augmentation for every analytical task: data pulls, pattern identification, RCA, BRD first drafts.
Build and maintain AI-powered workflows with ChatGPT, Claude, Cursor, or equivalent.
Surface new insights from client data: anomaly detection, ITC trends, and upsell signals.
Measure AI leverage monthly; target increases in AI-augmented output.
Lead Data BAs and Field BAs with structured 1:1s and performance reviews.
Set quality bars for output types: decks, BRD, RCA, and dashboards.
Run QBRs and manage enterprise client escalations with SLA discipline.
Own automation BRDs from BRD to UAT; ensure end-to-end delivery.
Build dashboards in Tableau/Power BI; ensure dashboards drive decisions.
Identify customization opportunities and push back when out of scope.

Skills

BA/Analytics

AI tools daily

Team leadership

Executive communication

BRD/FRD drafting

AI-driven insights

6+ years exp

Tools

SQL

Tableau/Power BI

Python scripting

ChatGPT/Claude/Cursor

Job description

ABOUT FINKRAFT.AI

Finkraft.ai is a B2B SaaS company that enables enterprises to maximise GST claims on travel and expense data. The platform automates invoice collection, validation, and reconciliation across airlines and hotels — helping finance teams at McKinsey, BCG, Capgemini, Abbott, and 1,250+ enterprises improve compliance, visibility, and cash recovery. We've recovered ₹300Cr+ in GST claims and are scaling from $1.5M to $10M ARR in 18 months.

THE OPERATING PHILOSOPHY OF THIS ROLE

AI-first is not a preference here. It is the baseline. Every analysis, every BRD, every QBR deck, every RCA, and every insight you produce starts with AI augmentation. If you are doing something manually that an AI agent could do faster and better, that is a process failure, not a workstyle choice.

This role exists because Finkraft's enterprise clients generate more data, more edge cases, and more expansion signals than any team can process without AI. You are the person who builds the system that processes it.

WHAT YOU WILL OWN IN 90 DAYS

AI-augmented analysis pipeline live: at least 3 recurring workflows (QBR prep, RCA, client health scoring) running through AI tools — output quality higher, turnaround time lower than manual baseline.
Team operating cadence set: weekly 1:1s and team standups running for both data BAs and field BAs, with structured output templates and quality bar defined.
Customisation pipeline tracked: live dashboard showing open customisation requests, delivery status, SLA compliance, and revenue attribution — reviewed weekly with BU Head.

SENIOR BUSINESS ANALYST — DATA & CLIENT INTELLIGENCE | FINKRAFT.AI
Location: Bengaluru, HSR(Onsite) | Full-time | Level: L4 |

ABOUT FINKRAFT.AI

THE OPERATING PHILOSOPHY OF THIS ROLE

WHAT YOU WILL OWN IN 90 DAYS

AI-augmented analysis pipeline live: at least 3 recurring workflows (QBR prep, RCA, client health scoring) running through AI tools — output quality higher, turnaround time lower than manual baseline.
Team operating cadence set: weekly 1:1s and team standups running for both data BAs and field BAs, with structured output templates and quality bar defined.
Customisation pipeline tracked: live dashboard showing open customisation requests, delivery status, SLA compliance, and revenue attribution — reviewed weekly with BU Head.

KEY RESPONSIBILITIES

AI-First Analysis and Insight Generation

Default to AI augmentation for every analytical task: data pulls, pattern identification, RCA structuring, QBR narrative drafting, and BRD first drafts
Build and maintain AI-powered workflows using ChatGPT, Claude, Cursor, or equivalent — document every workflow so the team can replicate it, not just you
Use AI agents to surface new insights from existing client data: anomaly detection, ITC trend analysis, reconciliation failure pattern identification, and upsell signal mining
Measure AI leverage monthly: what percentage of team output is AI-augmented vs. manual — target moves up every quarter, not sideways

Team Leadership — Data BAs and Field BAs

Manage and develop the data BA team (Ranjith's team): structured 1:1s, performance reviews, technical upskilling in SQL, dashboard tools, and AI workflows
Manage and develop the field BA team: output quality reviews, client observation structuring, and ensuring field findings translate into actionable product inputs within 5 business days
Set a clear quality bar for every output type — QBR deck, RCA document, BRD, dashboard — and hold the team to it without doing the work yourself
Run continuous recruitment for the BA bench: own the JD, screen applications, design the interview loop, and manage the onboarding ramp for every new BA hire

Automation BRDs

Author automation BRDs for engineering: reconciliation logic, validation rules, data transformation workflows, and exception handling — specific enough that engineering can build without a PM translation layer
Identify automation opportunities proactively — anywhere the team is doing something manually more than twice a week, evaluate whether it should be a BRD
Maintain a live automation backlog: prioritised, with business justification, effort estimates from engineering, and expected impact on client outcomes
Own automation delivery from BRD to UAT: you wrote it, you verify it works

Dashboard Ownership

Build and maintain dashboards in Tableau, Power BI, or equivalent: client health scores, issue resolution tracking, SLA compliance, customisation pipeline, and QBR trend data
Dashboards are not maintenance tasks — they are decision tools. Every dashboard you build must answer a specific question for a specific audience
Automate dashboard refresh where possible; reduce manual data preparation to zero on recurring dashboards
Present dashboard insights at weekly internal reviews and monthly BU Head reviews — proactive, not reactive

Enterprise Client Management and Push Back

Run QBRs for the BU's enterprise accounts: own the data pack, the trend narrative, and the action items — not just the slides
Manage enterprise client escalations that reach the Senior BA layer: investigate, respond within SLA, and close the loop in writing
Push back on client requests that fall outside scope, roadmap, or delivery capacity — clearly, with evidence, without damaging the relationship
Protect delivery timelines against scope creep: every new client request gets triaged, estimated, and formally accepted or declined — no informal commitments

Client Upselling Through Documentation

Build and maintain a upsell documentation library: ROI reports by client segment, value realisation summaries, customisation case studies, and expansion proposal templates
Produce value reports for top-25 accounts quarterly: what Finkraft has delivered, in numbers, against what was promised
Identify expansion signals in client data and QBR conversations; document them with specificity and hand off to Sales with context — not just a name and a note
Track upsell pipeline contribution from the BA layer: how many qualified opportunities identified, how many converted, what revenue attributed

Customisation Pipeline Ownership

Own the full customisation pipeline: intake, scoping, prioritisation, delivery tracking, and client communication
Set quarterly customisation targets with the BU Head: number of customisations delivered, average delivery time, SLA compliance rate, and revenue attributed
Report customisation pipeline status weekly to BU Head: open requests, in-development, delivered, and blocked — with clear owners and dates
Identify customisation patterns that signal a product feature: if 5 clients need the same customisation, it belongs on the product roadmap, not the customisation backlog

REQUIREMENTS

Must Have

6+ years in business analysis, data analytics, or consulting in B2B SaaS, fintech, or enterprise services
SQL at an advanced level: complex joins, window functions, aggregations, and query optimisation — not just basic selects
Tableau or Power BI: has built dashboards from scratch, not inherited and maintained
AI tools in daily workflow today: ChatGPT, Claude, Cursor, or equivalent — not experimentally, not occasionally, every day
Has managed a team of analysts or BAs: performance conversations, output quality standards, and difficult calls included
Has presented data-backed analysis to CFOs, tax heads, or equivalent senior client stakeholders — and answered hard questions in the room
Has written BRDs or FRDs that engineering shipped from without a PM translation layer

Strong Preference

Background in management consulting (Big 4, strategy houses) or a high-growth SaaS analytics function
Exposure to GST, indirect tax, travel expense management, or fintech reconciliation
Python or scripting skills for ad-hoc analysis and workflow automation
Has run a recruitment process end-to-end: JD to offer, not just participated in interviews