Data Engineering · India · UAE · Europe · North America
Production-grade ETL pipelines, data warehouses, and BI dashboards for FinTech NBFCs and D2C brands. Built against your actual data volumes. Handed over with full documentation and a 30-day support window.
3 wks → 2 hrs
Month-end reporting time
FinTech client, New York
99.8%
Data accuracy post-migration
was 91% in Excel
$180K / yr
Analyst hours recovered
same FinTech engagement
40%
Infrastructure cost reduction
logistics client, multi-cloud
Who this is for
Manual reconciliations, regulatory exports that take two weeks, and dashboards that no one trusts. We automate the entire data layer — pipelines from your core systems, RBI-compliant reports that generate themselves, and dashboards your finance team actually opens.
Post-purchase data is scattered across your ESP, ad platforms, and Shopify. CAC keeps climbing because attribution is wrong and churn is invisible. We build the data foundation, a single source of truth your marketing, retention, and product teams share.
What we deliver
The person who scopes your project is the same person who builds and delivers it. No handoffs. No junior engineers swapped in after the pitch.
01
Production pipelines from raw sources to clean, analytics-ready tables. Batch and real-time. Monitored, documented, handed over.
02
Snowflake, BigQuery, or Databricks designed for your query patterns and team size. Schema modelled for analysts, not engineers.
03
Dashboards finance and ops teams actually open. Built on your existing BI tool or a new one, tied to pipelines that update when your data does.
04
Automated regulatory report generation for NBFCs. Audit trails, reconciliation exports, and scheduled submissions — no analyst involvement required.
05
AWS-primary with Azure and GCP support. Infrastructure as Code so your team can reproduce, extend, and own the environment independently.
06
dbt tests, anomaly alerting, and row-count checks built into every pipeline. You know when data breaks before your users do.
Technology stack
Built with
How we work
01
We review your current stack, identify failure risks, and tell you exactly what needs fixing. No sales deck.
02
Fixed scope, fixed price, fixed timeline. You know the full cost before any work starts.
03
We build against your real data volumes and sources, not synthetic demos. Weekly progress updates.
04
Full documentation, runbooks, and a 30-day support window. Your team can operate it independently.
Why TryData
FAQ
Free audit
In 30 minutes we'll review your pipelines, identify the top failure risks, and give you a prioritised fix list. No cost, no sales pitch.