Head Data Team

Company: FinAGG Technologies Pvt. Ltd. Location: Noida (On-site) Level: Senior Leadership (7–12 years) Reporting to: CFO

FinAGG is an RBI-authorised MSME-focused fintech operating across credit intelligence (FameScore/FinAGG.ai), lending services, and NBFC infrastructure (QCF Capital). We have disbursed over ₹5,200 Cr to 85,000+ MSMEs across 6,200+ pin codes. Data is not a support function here — it is the product.

We are looking for a hands-on, analytically sharp leader to own the Data function end-to-end. This role sits at the intersection of lending analytics, MIS automation, and data engineering. You will build and lead a small, high-output data team that powers credit decisions, portfolio monitoring, anchor reporting, partner compliance, and internal business intelligence — all in a fast-moving fintech environment.

1. MIS & Reporting Automation

• Design and automate MIS frameworks for portfolio performance, collections, disbursements, and cohort analysis
• Build dashboards and scheduled reports for internal teams, anchor brands, and lending partners (banks, NBFCs)
• Eliminate manual Excel-heavy workflows; replace with scalable, automated pipelines

2. Lending & Credit Analytics

• Track portfolio health metrics — DPD buckets, delinquency trends, vintage analysis, repayment behaviour
• Support underwriting with data models, scorecard monitoring, and bureau data analysis
• Work closely with Risk & Collections Head on early warning signals and triggers

3. Data Churning & Transformation

• Own the data pipelines from raw sources (GST, bank statements, bureau, ERP, field data) to clean, analysis-ready datasets
• Manage data ingestion from multiple APIs and sources — GST Network, credit bureaus, banking partners
• Ensure data quality, reconciliation, and auditability

4. Platform & Product Data Support

• Partner with the CTO and product team to define data schemas, event tracking, and reporting layers for FinAGG's SaaS platform
• Support BRD and product documentation with data specifications

5. Regulatory & Partner Reporting

• Generate accurate reports for RBI-mandated disclosures, bureau submissions (CIBIL, Experian, CRIF), and lender covenant tracking
• Support audit readiness — internal and external (LSP audits, FDD, NBFC compliance)

Must-Have

• 6–10 years of experience in data/analytics roles, with at least 2–3 years in BFSI / fintech / lending
• Strong command of SQL (complex queries, window functions, CTEs) — non-negotiable
• Proficiency in Python or R for data wrangling, automation, and analysis
• Deep understanding of lending terminology — EMI, DPD, LTV, NPA, POS, disbursement flows, co-lending structures, bureau data fields
• Experience building or maintaining MIS dashboards (Power BI / Tableau / Metabase / Looker or equivalent)
• Hands-on with data pipeline automation — scheduling, orchestration, error handling
• Strong Excel/Google Sheets skills for ad-hoc analysis and stakeholder-facing outputs

Good to Have

• Exposure to GST data, bank statement analysis, or bureau data (CIBIL, Experian, CRIF)
• Familiarity with cloud data stacks — BigQuery, Redshift, Snowflake, or similar
• Experience in a startup or high-growth fintech environment
• Knowledge of RBI Digital Lending Guidelines and NBFC reporting norms
• Prior experience with supply chain finance, invoice discounting, or channel finance

• Someone who finds a broken MIS more offensive than a missed deadline
• Can move from raw data to a board-ready slide without losing accuracy
• Asks why does this number look wrong before presenting it
• Comfortable being the only data person in the room with a CFO, a Risk Head, or a bank partner
• Builder mindset — not just reporting on data but using it to surface insights no one asked for yet

• A seat at the table — this role has direct visibility with the founding team
• Ownership of the entire data stack in a company where data = moat
• Fast-moving environment with real complexity: multi-lender, multi-product, multi-channel
• Competitive compensation with ESOPs

Send your CV and a brief note on the most complex data problem you have solved in a lending/fintech context to [[Confidential Information]] with subject line: Head – Data Team | [Your Name]