If you can't trust the data, you can't trust the AI.
Data is siloed, ungoverned and lacks automated reconciliation. Every report raises the same questions: is this right, did every record arrive, and where is our sensitive information?
Sydney based · Australia wide
Your data platform doesn't need more tools. It needs to work harder for your business.
We build the trust and automation layer your existing data platform is missing: reliable migrations, automated quality and reconciliation, compliance by default and AI-ready foundations. Using the technology you already own.
Your ecosystem · Your IP · Our engineering
The missing layerTrust + automation
100%of database objects converted, validated and deployedCoal LSL
3 monthsto rescue a stalled SQL Server to AWS PostgreSQL migrationCoal LSL
99.9%data integrity and auditability across data layersMetLife
16+ yearsof hands-on enterprise data delivery behind every engagementFounder led
The bottleneckThe promise of the platform
The promise of the platform
vs. the reality of engineering.
Most organisations already own capable data platforms. What stalls them is the engineering bottleneck in between: stalled migrations, broken trust and manual pipelines.
Engineers stuck rebuilding the same things.
Teams are bogged down by repetitive manual onboarding, slow migrations and legacy platform maintenance, starving the business of the agility it bought the platform for.
Why we're different
The traditional consultancy model makes the bottleneck worse.
Most firms have something to sell alongside the service: a licence, a subscription, a proprietary accelerator. Our incentive runs the other way.
The traditional SI
The Data Guyz
Incentive
Licensing and vendor lock-in. Sell the tool.
Execution and resolution. Solve the problem.
IP ownership
Black box, vendor-owned IP.
Transparent, client-owned IP built in your ecosystem.
Technology
Push net-new enterprise software.
Maximise your existing stack: SQL, Python, metadata.
Delivery
Heavy partner-level overhead.
Lean specialist pods who write the code.
Practical engineering. Real business outcomes.
Use what you have. Build what you need. Own what you build.
We install the reliable pipelines, trusted reporting and automated governance controls that sit between a data platform's promise and the business value it is expected to deliver.
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Use what you have
We look at your existing investments across Google Cloud, Azure, AWS, Snowflake and Databricks, and work out whether the problem can be solved inside that ecosystem first. No unnecessary software.
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Build what you need
Where capability is missing, we engineer it using SQL, Python, metadata and AI: pipelines, frameworks and automation built around your real requirements, not another tool.
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Own what you build
The IP, configuration-driven frameworks and implementation logic stay in your environment, documented so your team can run and extend them. No vendor lock-in.
What we doThe capabilities you need.
The capabilities you need.
The flexibility to deliver them.
Four capability areas, delivered inside your existing environment so the IP, the control and the knowledge stay with you.
Data engineering & platforms
Batch and incremental pipelines, ELT/ETL, medallion architectures, SQL, Python, PySpark and API-based integration.
Explore →Quality, governance & privacy
Automated reconciliation, PII classification and masking, load audit frameworks and controlled data disposal (ADDF).
Explore →Migration & modernisation
Legacy-to-cloud database conversions, schema mapping, migration rehearsals, reconciliation and cloud cost optimisation.
Explore →AI readiness & enablement
Trusted foundations for BI, enterprise knowledge search with Snowflake Cortex, and AI-assisted onboarding (Noviq) and migration (Noviq Shift).
Explore →The trust and growth foundationReal problems. Real data.
Real problems. Real data.
Real results.
Four engagements across the data lifecycle: migrate, govern, comply and activate. One consistent method, all built on existing infrastructure.
Coal LSL
Rescuing a stalled cloud migration
SQL Server → PostgreSQL on AWS
The AWS migration was slipping for lack of specialist skills. Every table, view, stored procedure and function was converted, validated against source and reconciled at each step.
100% in 3 monthsObjects converted, validated and deployed, with audit-ready documentation.
MetLife
Automated data quality and load audit
Snowflake · Matillion · SQL
A SQL-based data quality framework MetLife can extend, a load audit layer on Matillion showing source vs. target counts per layer, PII classification and an organisation-wide data dictionary.
99.9%Data integrity and auditability, with significantly less manual effort.
The Smith Family
Automated data disposal and de-identification
Azure Synapse · Azure SQL · Fabric · Power BI
ADDF purges data at the end of its retention period on schedule, de-identifies what must be kept for analysis, and reports what has been disposed of and what's next.
Compliant by defaultReduced regulatory risk and audit-ready transparency.
The Smith Family
Making scattered knowledge searchable
Snowflake Cortex · Openflow · ADLS
Two optimised pipelines bring Zendesk knowledge base articles and SharePoint files into Snowflake Cortex Search, without a custom integration layer.
AI-ready knowledgeMultiple sources unified in one searchable environment.
Client testimonials
The Data Guyz demonstrated deep technical expertise, excellent coordination, and a true sense of ownership that made this migration one of the smoothest technology transitions we've experienced. We'd gladly recommend them for any high-stakes data engineering or platform modernization work.
Tim Gardner, Data Platform Manager, Coal LSL
Neeraj and his team are highly professional, detail-oriented, and collaborative. Their deep technical expertise and proactive problem-solving made a measurable impact on our data ecosystem. We'd be happy to recommend The Data Guyz for any data engineering, governance, or analytics initiatives.
Srilata Nutakki, MetLife
Notice what was missing?
We didn't sell them a single new software platform.
In every engagement, from complex cloud migrations to enterprise-grade AI search, we installed the trust and automation layer their existing stack was missing. The logic was written directly in their ecosystem.
Your ecosystemYour IPOur engineering
The growth acceleratorsStop paying engineers
Stop paying engineers
to rebuild from scratch.
Noviq helps you bring new data in. Noviq Shift helps you move what you already have. We productised the engineering discipline behind our case studies so you move faster, deployed inside your environment.
Noviq
AI-based data onboarding · Data engineering & governance
- Dataset discovery: analyses source files to identify structure, schema and data characteristics.
- AI recommendations: suggests data types, candidate keys, metadata and partitioning.
- Human in the loop: engineers and business users review and override before any code is generated.
- Implementation artefacts: generates mappings and technical documentation automatically.
ValueReduces new data onboarding timelines by up to 80%.
Noviq Shift
AI-based data migration · Database modernisation & ETL conversion
- Asset analysis: identifies database objects, ETL assets and dependencies.
- Conversion assistance: helps convert SQL and ETL logic between supported platforms.
- Compatibility insights: surfaces conversion gaps and anything needing manual review early.
- Validation support: assists with source-to-target checks and reconciliation.
ValueSlashes manual effort for repeatable migration workloads and accelerates reconciliation.
16 years of enterprise delivery
Enterprise-grade thinking. Delivered by the people who write the code.
Neeraj 'Rohan' Choraria · Founder & Principal Architect
16+ years of hands-on data architecture and engineering, combining Big Four delivery standards from Deloitte with deep engineering execution across cloud modernisation, automated data quality, privacy and PII frameworks, configuration-driven engineering and LLM-powered metadata generation.
Woolworths GroupTransport for NSWIAGOptus
SEEKNSW HealthNDISDeloitte
"I've spent 16 years seeing the same data problems appear in different organisations. The technology changes. The problems don't."
The founder
Hands-on delivery across some of Australia's most complex data environments.
The pattern
Complex migrations, automated reconciliation, PII governance and legacy modernisation, solved again and again.
The team
A growing specialist firm, including experts like Aditya and Damon, delivering Big Four quality at a fractional cost.
Google Cloud Professional Cloud Architect · Snowflake SnowPro Core · Microsoft Azure Data Analyst Associate
CredentialsCertified expertise.
Certified expertise.
Flexible delivery.
Big Four quality, zero vendor lock-in, at a fractional cost, because there's no partner-level overhead baked into the pricing.
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Google Cloud PartnerGCP Cloud Partner
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SnowflakeRegistered Partner
A
Anthropic Claude Partner NetworkRegistered tier
How we work
Engagement models that fit the work.
Start with a defined outcome, a focused squad or senior specialists inside your team. We'll recommend the model that matches your problem on the discovery call.
01
Project delivery (fixed SOW)
End-to-end accountability for a specific architectural build or migration.
02
Specialist squads
A highly aligned team of data engineers dropped into your ecosystem to clear a backlog.
03
Staff augmentation
Senior experts embedded in your existing team to upskill and accelerate delivery.
Microsoft FabricAzure Data FactoryAzure SynapseDatabricksSnowflakeSnowflake CortexBigQueryGoogle CloudAWSPostgreSQLMatillionPySparkSQLPower BI
Trust your data. Move faster.
Build the capability you actually need.
Bring us one real data problem and let's explore how to solve it using the ecosystem you already own. No new licences required.