Data Engineering Services
That Turn Raw Data Into Decisions
Your data is scattered across systems, inconsistent, and hard to trust. We design and build the pipelines, warehouses, and reporting layers that make your data a reliable asset — not a liability.
The Full Data Engineering Stack
From source system extraction to business intelligence layer — we design, build, and maintain the data infrastructure your organization needs to make decisions with confidence.
ETL / ELT Pipeline Design
Extraction, transformation, and loading pipelines designed for reliability, idempotency, and observability. We build pipelines that fail gracefully and recover automatically.
Data Warehouse Architecture
Star schema and Data Vault design for SQL Server, Azure Synapse Analytics, and Azure SQL. Built for analytical query performance, not just storage.
Azure Data Factory Pipelines
ADF pipeline design, parameterization, monitoring, and optimization — including integration with Data Lake Storage Gen2, Databricks, and Azure SQL targets.
Python Data Automation
Custom Python scripts and packages for data extraction, API integration, data quality checks, orchestration, and business process automation using pandas, SQLAlchemy, and Airflow.
Power BI & Reporting Layer
Data model design, DAX measure development, report and dashboard creation, row-level security, and Power BI Gateway configuration for on-premises data sources.
Data Quality & Governance
Data profiling, quality rule implementation, lineage documentation, and metadata management — so your organization can trust the numbers it reports and acts on.
The Tools We Use Every Day
We specialize in the Microsoft data platform and complement it with the best open-source tools in the ecosystem.
Azure Data Factory
Pipeline orchestration, triggers, linked services, and integration runtimes — including self-hosted IR for on-premises connectivity.
Azure Synapse Analytics
Dedicated and serverless SQL pools, Synapse Pipelines, and integration with Data Lake for large-scale analytical workloads.
SQL Server & Azure SQL
Transactional source systems, staging databases, data marts, and analytical stores — covering the full spectrum of SQL-based data infrastructure.
Python (pandas, SQLAlchemy, Airflow)
Data transformation, API integration, orchestration, and custom ETL logic where visual tools are insufficient.
Pentaho Data Integration
Enterprise ETL workflows with Pentaho Kettle for organizations with existing Pentaho investments or complex transformation requirements.
Power BI
From data model design to published dashboards — including incremental refresh, composite models, and enterprise-grade deployment pipelines.
From Data Chaos to Reliable Pipelines
Data Landscape Assessment
We map your existing data sources, understand business reporting needs, and document data quality issues and integration gaps.
Architecture Design
We propose a data architecture (warehouse, lakehouse, or hybrid) that fits your current scale and planned growth — with technology choices justified by your constraints, not trends.
Pipeline Development
Iterative development of ingestion, transformation, and loading layers with automated testing and data quality checks at each stage.
Reporting Layer
Semantic model design and Power BI report development aligned with the business metrics your stakeholders actually use.
Handoff & Documentation
Full technical documentation, runbooks for operations, and knowledge transfer sessions so your team can maintain and extend the platform.
Data Engineering Questions
We have no data infrastructure at all. Where do we start?
We start with a 1–2 week discovery engagement to understand your data sources and business reporting needs, then propose a phased roadmap that delivers value incrementally rather than a 12-month mega-project.
Can you work with our existing on-premises SQL Server and ERP systems?
Yes. Most of our clients have a mix of on-premises ERP (SAP, Dynamics, custom), legacy SQL Server databases, and cloud services. We specialize in integrating heterogeneous source systems.
Do you offer ongoing data engineering support after the initial build?
Yes. We offer retainer-based data engineering support for pipeline monitoring, new source integrations, schema evolution handling, and report extensions as your business grows.