Enterprise Data Modelling
Conceptual, logical, and physical models tied to source-system reality. Conformed dimensions, slowly changing dimensions, and a glossary the business actually owns.
- Conformed model
- Source mapping
- Glossary
Senior data architects who handle modelling, warehouse and lakehouse design, ETL and streaming pipelines, master data, and governance. Onboarded inside your VPC, on your cloud, on your sprint cadence from day one.
Trusted by enterprises across Retail, Manufacturing, BFSI, Logistics, and FMCG
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With 24+ years of enterprise delivery and a bench of 500+ engineers, orangemantra ships data architects who own the blueprint end-to-end: modelling, warehouse and lakehouse design, integration patterns, master data, and governance.
Most enterprises do not lack data. They lack a single source of truth, a documented model, and a pipeline owner who can defend the numbers. Hire data architects who unify fragmented systems, retire shadow warehouses, and put governance in the path of every release. Pair them with hire data engineers when the brief needs both blueprint and build.
Core Data Architecture Capabilities
Every engagement moves through these three layers. Hire data architects who own each one end-to-end, not specialists who hand off the blueprint before the build starts.
Conceptual, logical, and physical models that pin business meaning to schema. Source-system mapping, conformed dimensions, and a single version of every entity.
Cloud warehouse, lakehouse, and streaming layers wired together with ETL, ELT, and CDC patterns. Reproducible deployments, version-controlled transforms, and clear cost guardrails.
Lineage, data quality tests, access controls, and PII handling baked into the pipeline. Catalogue, glossary, and ownership defined before the first dashboard ships.
Pre-vetted data architects ready to start inside a fortnight. The bench covers warehouse, lakehouse, MDM, and governance without recruitment lag.
Every model, table, and pipeline is justified by a real question the business asks. No speculative entities, no orphan dashboards.
Comfortable across Snowflake, Databricks, BigQuery, Redshift, Synapse, and on-prem warehouses. The right platform for the workload, not the loudest brand.
Working warehouse or lakehouse foundation in four to eight weeks, then a hardened path to scale with lineage, tests, and cost dashboards.
Hire data architects who plan around source-system maturity, compliance posture, and procurement cycles, not a templated migration playbook.
If a pipeline breaks at 2 am, the data architects for hire are a Slack ping away. Coverage windows are set on the engagement, not a generic SLA card.
The right blueprint depends on volume shape, data residency, and how much governance the business can defend. Hire data architects who frame the trade-off before they draw a single diagram.
Best when reporting and finance need a single source of truth fast. Architects scope Snowflake, BigQuery, or Redshift with conformed dimensions, medallion layers, and dbt transforms tied to source-system reality.
Databricks or open Delta and Iceberg patterns when ML and BI need to live on the same tables. Pairs well when you also hire big data developers to build the streaming and Spark side of the estate.
For enterprises that cannot agree on a customer or product record across ERP, CRM, and commerce. Architects design the hub, the survivorship rules, and the stewardship workflow that keeps it clean.
Kafka, Kinesis, and CDC-driven pipelines for fraud, logistics, and personalisation. Sub-minute serving layers wired to the same governed model as your batch warehouse.
For regulated estates with on-prem warehouses that still need to grow. Architects design the hybrid path, parallel-run windows, and the data contract that keeps both sides aligned during transition.
Short, sharp engagements to audit an existing warehouse or lakehouse, surface cost and quality risk, and produce a remediation plan you can act on next sprint.
Hire data architects who build for line items finance can verify: faster close, fewer manual reconciliations, lower warehouse spend, cleaner audits, and shorter time to a usable dashboard.
Explore your data use caseAI's impact on businesses is undeniable and immeasurable. Gear up with the orangemantra data architecture team.
The hiring path is built around enterprise procurement reality, not freelancer marketplaces. NDA on day one, profiles inside 48 hours, interviews on your schedule, and onboarding through your security stack.
Start the Hiring BriefA 30-minute call to map data sources, current warehouse pain, compliance posture, and the shape of the team needed: lead architect, warehouse specialist, governance owner, or migration lead.
Three to five vetted data architects, ranked against the brief with prior architecture artefacts, platform certifications, and rate cards. No bait-and-switch profiles.
Technical interview on your terms, optional paid trial sprint, and reference checks. Replace any architect at no extra cost inside the trial window.
Architects onboard to your identity provider, repos, ticketing, warehouse, and data perimeter. Delivery cadence locks to your sprint rhythm from week one.
Data architecture economics shift by sector. The team scopes the foundation to where the reconciliation load, audit pressure, or analytics gap is already heaviest. The same delivery floor supports AI, ML and data analytics solutions built on top.
General-ledger and sub-ledger reconciliation, regulatory reporting, and PII-aware analytics under model risk management.
Unified product, customer, and order data across Shopify, Magento, and ERP. Same model serves merchandising, finance, and marketing.
SCADA, MES, and ERP data unified so OEE, scrap, and downtime line up against a single quality model.
Carrier, TMS, and warehouse data joined for end-to-end visibility, demurrage signals, and driver KPI reporting.
EMR, claims, and operational data architected under HIPAA-aware guardrails with PHI redaction at ingest.
Booking, PMS, and loyalty data unified into one revenue and guest model so pricing and CRM teams stop debating numbers.
A working data foundation is a stack, not a single warehouse. Hire data architects fluent across modelling, platform, orchestration, governance, and BI layers.
Snowflake
Databricks
Google BigQuery
Amazon Redshift
Azure Synapse
PostgreSQL
MySQL
Microsoft SQL Server
Oracle
MongoDB
Apache Cassandra
Apache Airflow
dbt
Apache Kafka
Apache Spark
AWS Lake Formation
Tableau
Looker
QlikThree models, one delivery floor. Switch between them as the programme moves from audit to migration to long-running governance, without re-signing a master agreement. Need analytics or science profiles too? Pair with hire data scientist.
The first sprint usually delivers an audit and a target architecture. The next two harden it: conformed models, tested pipelines, lineage, and cost dashboards before any new BI traffic moves over.
Talk to Our TeamReal reviews from teams that have shipped with orangemantra. Verified on Clutch and GoodFirms.
"The architects came with the model on paper before they touched the warehouse. That alone made every later conversation defensible."
Apr 2025
Feedback SummaryOrangemantra data architects designed a Snowflake foundation with conformed finance and customer models, dbt transforms, and an audit-ready lineage layer. Period-end close timelines shortened meaningfully.
"They cut our warehouse spend by a meaningful margin and gave merchandising a model they actually trust."
Sep 2025
Feedback SummaryA two-architect pod designed a Databricks medallion lakehouse for a Shopify-plus retailer, with conformed product and customer models, dbt transforms, and Unity Catalog governance.
"Onboarded inside our VPC on day one. The migration ran in parallel for eight weeks, then cut over without a single late report."
May 2025
Feedback SummaryOrangemantra delivered an on-prem to BigQuery migration with reverse-ETL into operational systems, parallel-run validation, and a documented rollback path. Audit findings closed inside the same engagement.
"They built the governance posture first, then the model. Audit no longer asks the same questions twice."
Aug 2025
Feedback SummaryThe engagement designed a master data hub across ERP and CRM, match-and-merge rules, a stewardship workflow, and a catalogue with PII tagging. Quality SLAs delivered alongside the handover.
Independent recognition from industry bodies and analyst platforms. Listed only where verifiable.
CIO Choice
Top IT Service
WARC Award
Globus
NASSCOM
ISO Certified
A data architect designs how data moves, lives, and is governed across an enterprise. The role covers modelling, warehouse and lakehouse design, integration patterns, master data, security, and lineage so analytics and operational systems can trust the same numbers.
Senior data architect rates vary by region, scope, and stack maturity. A short engagement for modelling and warehouse design sits in the lower tens of thousands of dollars; a full enterprise data foundation programme bills by sprint. Orangemantra shares a fitted estimate after a scoping call.
A data architect typically carries a higher rate than a data engineer because the role owns the blueprint, not just the build. A data architect chooses the model and platform path; a data engineer implements pipelines against that blueprint.
Most engagements move from first call to billable work inside five to ten business days. Profiles arrive within 48 hours of the brief, interviews run on your schedule, and onboarding happens inside your VPC and identity provider.
Yes. Orangemantra offers full-time dedicated data architects, part-time engagements for review and design sprints, and hourly rotations for audits or migrations. The same bench also covers data engineers, big data developers, and analytics specialists.
Orangemantra data architects work across Snowflake, Databricks, BigQuery, Redshift, Synapse, and on-prem warehouses; modelling tools such as ERwin and dbt; orchestration through Airflow, ADF, and Fivetran; and governance platforms including Collibra, Alation, and AWS Lake Formation.