Pipelines, lakes and warehouses on Azure, secured and automated.
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§ Signs
We build and run data platforms on Microsoft Azure as a Microsoft partner. Our Azure data engineering services cover Azure Data Factory pipelines, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL Database and Managed Instance, and Azure Databricks integration. We develop ETL and ELT pipelines with incremental loads and CDC, secure them with Key Vault and Managed Identity, and deploy them through Azure DevOps CI/CD. Orchestration, monitoring and alerting keep pipelines visible, while governance and security keep data protected as you migrate and modernize on Azure.
Most Azure data estates grow one pipeline at a time. These are the symptoms of growth without a plan.
Changes are made directly in production with no Git, no review and no way to roll back.
Connection strings and passwords sit inside linked services or notebooks instead of Key Vault.
Every table is reloaded in full because there is no incremental load or change data capture.
Dedicated SQL pools and clusters run around the clock, whether anyone is using them or not.
One self-hosted integration runtime on one VM carries every on-premises load.
§ What we deliver
Choose an area to see the services in it.
Azure Synapse AnalyticsAzure Data Lake Storage Gen2Azure SQL DatabaseAzure SQL Managed InstanceAzure Data FactoryAzure Key VaultAzure DevOps§ Proof
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§ Approach
We map sources, existing pipelines, Azure subscriptions and security requirements.
You receive Azure data platform assessment
Lake zones, Synapse or Azure SQL design, Databricks integration and the security model are agreed up front.
You receive Azure data architecture and security design
We set up managed identities, private endpoints, Key Vault and least-privilege access on the lake before any production data arrives.
You receive Identity, network and access design
ADF pipelines and ELT logic are built as code, parameterized for each environment.
You receive Parameterized pipelines in source control
Azure DevOps pipelines deploy data workloads; orchestration, monitoring and alerts are configured.
You receive CI/CD pipelines, alert rules and dashboards
We migrate remaining on-premises workloads to Azure and support the platform in production.
You receive Migration plan and runbooks
§ Tech stack
Azure Data FactoryAzure Synapse AnalyticsAzure Data Lake Storage Gen2Azure SQL DatabaseAzure SQL Managed InstanceAzure Key VaultAzure DevOpsAzure Monitor§ Engagement models
A defined scope, timeline and deliverables, from design through go-live.
An agreed price for a clearly scoped implementation, such as a migration or a new warehouse.
Our engineers work under your contract, or as a subcontractor to consulting firms and system integrators.
Data engineers who join your team and work in your tools and processes.
Consultants and developers working remotely, with overlap in your working hours.
Architecture reviews, platform choices and design guidance for your own team.
Monitoring, incident handling and ongoing fixes for pipelines and databases in production.
A short, fixed-scope engagement to test an approach on your data or plan a migration.
§ FAQs
Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL Database, Azure SQL Managed Instance, Azure Databricks, Azure Key Vault and Azure DevOps.
Yes. We build ETL and ELT pipelines with incremental loads and CDC, so only new and changed data is moved on each run.
We integrate Azure Key Vault and Managed Identity, so pipelines authenticate without stored passwords or keys.
Yes. We use Azure DevOps to version, test and deploy data pipelines across development, test and production environments.
Yes. Azure data migration and cloud modernization includes moving SQL Server databases to Azure SQL Database, Managed Instance or Synapse, with validation before cut-over.
Data Factory remains a dependable orchestrator, and Azure Databricks with ADLS is a strong engineering platform. Microsoft now ships most new analytics features in Fabric, so for new builds we assess Fabric first and recommend it where it fits your workloads and licensing.
Budgets and alerts per environment, pausing dedicated SQL pools when idle, serverless SQL for ad hoc queries, storage lifecycle policies and right-sized integration runtimes and clusters.
Yes. We follow your subscription model, naming, tagging and Azure Policy, and request changes through your normal approval process.
One set of generic pipelines driven by a control table that lists sources, load type and schedule. Adding a source becomes a configuration change, which keeps the pipeline count small and behavior consistent.
Yes. We use Event Hubs with Stream Analytics, Azure Databricks or Fabric Eventstream, depending on latency needs and where the data is consumed.
§ In detail
Resource groups, ADLS Gen2 containers per layer, naming and tagging, aligned with your existing Azure landing zone.
Parameterized Data Factory or Synapse pipelines where adding a source means adding a row to a control table, not building a new pipeline.
Managed identities, RBAC and ACLs on the lake, private endpoints and Key Vault for every secret.
Bicep or ARM templates and Azure DevOps or GitHub Actions releases across development, test and production.
Azure Monitor and Log Analytics alerts for failed runs, plus budgets and cost alerts per environment.
Architecture diagrams, data flows and runbooks your operations team can use on day one.
We work within your subscriptions, Azure Policy and approval process, not around them.
Private endpoints and firewall rules often have the longest lead time, so we raise them in week one.
Every resource is defined in templates your cloud team can review like any other change.
Delta tables on ADLS keep the option to adopt Microsoft Fabric later through OneLake shortcuts.
Private networking, customer-managed keys where required and audit logs retained for review.
Encryption at rest and in transit, access reviews and data kept in the Azure regions you choose, in line with HIPAA and state privacy rules.
Shipment and telematics events through Event Hubs, landed in the lake for near-real-time status reporting.
Tenant-separated storage and pipelines that load each customer's data without mixing it with another's.
§ Contact
Tell us about your Azure estate and what you need your pipelines to do.
