Data Engineering & Consulting
for Enterprise-Scale Outcomes
We design, build, modernize, and optimize enterprise data platforms that make your existing stack work harder — without adding tools, vendors, or complexity
ISG Noteworthy Provider
Advanced Analytics & AI (2025)
A Track record of Excellence
Since 2016
ISO 27001 Certified
Global Security Standards
Industry Partnerships
Databricks, Snowflake, Microsoft
Most enterprises don't lack data
they lack the expertise to use it
After years of platform investments, the reality for most mid-to-large enterprises is a fragmented, expensive, and underperforming data landscape.Tools accumulate. Pipelines break. Teams firefight. ROI disappears into complexity. This is the problem Ignitho was built to solve, not by adding more technology, but by applying Frugal Innovation: making what you already own work at its full potential
Manual bottlenecks & pipeline debt
Complex ETL pipelines requiring extensive manual maintenance, causing IT dependency and delivery delays that block business decisions
Disconnected data silos
Data trapped across cloud APIs, legacy files, and SaaS platforms — fragmented ecosystems that make unified reporting impossible without manual intervention
Data quality & decision risk
Frequent inconsistencies and errors in source data that cascade into unreliable dashboards, delayed board reporting, and flawed strategic decisions
Cloud cost overruns
Poorly optimized queries, uncompressed data formats, and over-provisioned infrastructure that inflate cloud bills while delivering no additional insight
of enterprises say messy data blocks their AI readiness
average time to hire a senior data engineer in the market
of data engineering time spent on manual pipeline fixes
higher cloud cost when ETL pipelines are not optimized
What We Deliver
Our data engineering practice covers the full data platform lifecycle — from raw ingestion through to business-ready intelligence layers. Every engagement is anchored to your existing technology investments, not a new vendor stack
Real-Time Data Streaming & Pipeline Engineering
Build event-driven, low-latency data pipelines that move, transform, and validate data at speed. We architect streaming infrastructure on Kafka, Kinesis, and Azure Event Hubs — enabling real-time decisioning, fraud detection, and operational intelligence without overhauling your existing landscape
Modern Data Warehouse & Lakehouse Design
Architect scalable, cost-efficient data warehouses and lakehouses on Snowflake, Databricks, and cloud-native platforms. We migrate legacy systems, implement medallion architectures, and establish data contracts that make your warehouse a reliable source of truth — not a maintenance liability
ETL/ELT Pipeline Optimization & Reliability Engineering
Rescue, stabilize, and optimize broken or inefficient data pipelines. We audit existing ETL processes, rewrite poorly performing transformations, eliminate manual interventions, and implement robust error-handling and monitoring, reducing cloud compute costs and eliminating the overnight failures that derail morning reporting cycles
Cloud Migration &
Platform Modernization
We execute low-risk, high-fidelity migrations from legacy Oracle, SQL Server, and Teradata estates to modern Snowflake or Databricks platforms on AWS and Azure. Our methodology ensures zero disruption by running parallel workloads and validating data parity before a confident cutover. Post-migration, we aggressively optimize cloud consumption through restructured partitioning and query patterns—regularly slashing cloud bills by 30–50% to ensure long-term cost efficiency
Data Quality, Governance & Observability
Implement data quality frameworks, automated testing pipelines, and observability tooling that give your teams confidence in every dataset. We build Great Expectations suites, Monte Carlo integrations, and dbt test layers that catch issues before they reach the business. Compliance-ready for GDPR and HIPAA regulated environments
Data Platform Architecture & Consulting
Independent advisory to help CDOs, CIOs, and Heads of Data Engineering evaluate their current architecture, make stack decisions, and build a pragmatic 12-to-24-month data platform roadmap. No vendor bias. No tool pushing. Just clear, commercially grounded guidance that protects your existing investments while charting a credible path forward
From discovery to production
in weeks, not quarters
Ignitho’s delivery model is anchored in short, outcome-focused cycles. We do not run long discovery phases, produce dense architecture documents, and then disappear for six months. Every phase produces a tangible, measurable deliverable
7-Day Triage &
Discovery
Rapid assessment of your current data stack, pipeline inventory, and key pain points
Sprint Zero-Architecture & Planning
Define the target architecture, data contracts, and delivery milestones
Iterative Delivery -7 to 30-Day Sprints
Specialist POD teams execute in tight, outcome-driven sprints
Stabilize, Optimize & Handover
Production hardening, performance tuning, documentation, and team enablement
Specialist PODs
self-contained, outcome-driven, Day-1 productive
Ignitho deploys self-contained Specialist PODs: cross-functional delivery units that combine Human Intelligence (senior practitioners), Artificial Intelligence (automation and AI agents), and Technology Intelligence (your existing platforms). Each POD integrates into your existing Agile/Jira workflow on Day 1. There is no ramp-up theatre, no management overhead, and no hand-holding required. Your engineers get time back, not a new team to manage
Single point of accountability
One POD Leader owns delivery and acts as your primary interface. No diffuse responsibility, no finger-pointing between teams
Agile velocity
Short, continuous delivery cycles with visible progress at every sprint review. Business stakeholders see outcomes, not activity metrics
Plug-and-play integration
Works within your existing tools, governance frameworks, and operating models. No disruptive change management. No rip-and-replace mentality
AI-augmented delivery speed
Automated data quality validation, AI-assisted code review, and accelerator libraries built into the POD reduce delivery time by up to 40%
Solving your data problems, big or small
Flexible Engagement Models
From clearing a pipeline backlog in two weeks to running a multi-year modernization programme.Ignitho has an engagement model that fits your urgency, budget, and risk appetite
Tactical Intervention
Broken pipelines, dashboard backlogs, urgent board deadlines, or a stalled proof-of-concept that needs rescuing
- Accelerated Task Force deployment in days
- No long-term MSA required to start
- Clears technical debt and stalled backlog immediately
- Fixed-scope, fixed-outcome delivery
- Ideal for: quick wins before a board or audit event
Agile Scaling
Most Requested →
Internal teams overwhelmed by maintenance, or facing a 4+ month hiring delay for senior data engineers
- Self-governed Specialist POD embedded in your team
- Integrates with your existing Agile/Jira workflow
- Senior practitioners from day one, no ramp-up theatre
- 7 to 30-day iterative sprint cycles with visible outcomes
- Ideal for: ongoing data platform delivery at velocity
Strategic Transformation
Modernizing full data stacks to Snowflake or Databricks, or building an enterprise-wide data strategy and AI readiness programme
- Managed Outcome Partnership with full delivery ownership
- Architecture advisory and platform decision governance
- Multi-POD coordination across workstreams
- Measurable ROI milestones and shared accountability
- Ideal for: CDO/CIO-led transformation programmes
*All engagements can begin under a specialist waiver — bypassing PSL bottlenecks for niche, high-velocity data work
Proven results across regulated, complex industries
Eliminating underwriting leakage - from 8 hours to 15 minutes
A major business insurer faced revenue leakage from quality issues in manual underwriting evaluation. Underwriters spent entire working days on low-value document review instead of high-value decisioning. Ignitho implemented LLM-powered AI agents with RAG architecture to automatically process hundreds of policy pages, with Explainable AI allowing underwriters to interrogate agent logic and ask follow-up questions. Result: decision cycles collapsed from a full working day to 15 minutes, with 100% data capture ensuring full regulatory compliance.
- 96% cycle time reduction
- 100% data capture compliance
- Explainable AI governance
- LLM + RAG architecture
Automating 80% of ML workflows via AWS SageMaker
Legacy ML models couldn’t provide real-time campaign guidance and suffered from manual scaling failures across global markets. Ignitho re-platformed into AWS SageMaker with automated error-handling and OLTP-to-OLAP migration, enabling leaders to pivot campaign selection on live statistics
- 80% automation of model execution
- Real-time campaign guidance
- AWS SageMaker migration
Eliminating revenue guesswork with dynamic forecasting
Marketing teams couldn’t predict total revenue before committing to campaign launches. Ignitho built a self-adjusting dynamic forecasting model that ingests live sales data and updates projections daily — giving leadership pre-launch clarity and reducing planning cycles by 40%
- 40% forecast accuracy improvement
- Daily self-adjusting model
- Eliminated manual spreadsheets
Increasing audit operational efficiency by 70% with NLP
Marketing teams couldn’t predict total revenue before committing to campaign launches. Ignitho built a self-adjusting dynamic forecasting model that ingests live sales data and updates projections daily — giving leadership pre-launch clarity and reducing planning cycles by 40%
- 70% efficiency gain
- 80% error reduction
- IFRS + Basel III native
Why Ignitho
The specialist advantage — depth over breadth
Large generalist SIs excel at macro strategy and infrastructure moves. Ignitho fills the execution gap they leave behind the pipeline optimization, the cloud cost leakage, the integration work that falls between the cracks. We are intentionally non-disruptive and designed to complement, not replace, your existing partners
Non-disruptive by design
We complement your existing vendors and internal teams. No rip-and-replace. No disruptive change management programs
Day-1 Productive teams
Senior practitioners who know Snowflake, Databricks, and AWS better than most internal teams. No ramp-up theatre. No hand-holding
Frugal Innovation principle
Grounded in Cambridge research. Maximum impact from existing investments. No new licensing. No tool bloat. Lower total cost of outcome
Outcomes, not activity
Measured by business results, not hours billed. Every sprint closes with a deployed, tested, business-ready deliverable
Global delivery, local presence
US HQ in Tampa. On-the-ground presence in the UK, Sweden, India, and Costa Rica. Flex onshore/offshore/hybrid to match your governance model
Enterprise-grade security
ISO 27001 certified. SOC 2 compliant. Robust data privacy controls for GDPR and HIPAA regulated environments
Named “Noteworthy Provider” in Advanced Analytics & AI
Independently validated for enterprise-grade delivery. Ignitho is recognized for its specialist approach to data engineering and applied AI — delivering measurable outcomes without the overhead of generalist transformation programs.