Data Engineering
Every data problem eventually becomes the same problem: nobody trusts the number. Reports disagree, pipelines break silently, and teams go back to their own spreadsheets.
All servicesCapabilities
Our Data Engineering Services
Data Strategy & Governance
- Data maturity assessment
- Target data architecture
- Governance operating model and ownership
- Data catalog and lineage
- Access control and privacy compliance
- Metric definitions and semantic standards
Data Pipeline & Integration Engineering
- ETL and ELT pipeline development
- Source system and API integration
- Change data capture
- Ingestion from ERP, CRM, SaaS, IoT and databases
- Orchestration and scheduling
- Pipeline testing and observability
Real-Time & Streaming Data
- Event streaming architecture
- Streaming ingestion and processing
- Event-driven and CDC pipelines
- IoT and telemetry data processing
- Operational and near-real-time dashboards
Business Intelligence & Analytics
- Semantic layer and metric modeling
- Interactive dashboard development
- Self-service analytics enablement
- Operational and regulatory reporting
- Exploratory data analysis
- Embedded analytics
Data Warehouse & Lakehouse Engineering
- Dimensional and data vault modeling
- Cloud data warehouse implementation
- Data lake and lakehouse architecture
- Medallion layer design
- Partitioning, clustering and query tuning
- Storage cost optimization
Data Quality, Migration & Modernization
- Automated data quality and validation frameworks
- Legacy warehouse and database migration
- On-premises to cloud modernization
- Reconciliation and parallel-run validation
- Master data management
- Performance and cost optimization
Why Arocom
Why Arocom for Data Engineering
Reliability is a feature
Pipelines ship with tests, freshness checks, alerting and documented recovery - so failures surface before a stakeholder finds them.
Modeled for how the business asks questions
We design warehouse schemas around real reporting needs, which is why dashboards stay fast and definitions stay consistent.
One definition per metric
Governed semantic layers and clear ownership mean "revenue" means the same thing in every report.
Built to feed what comes next
Clean, well-governed data is what makes AI and advanced analytics possible - so we engineer for that from the start.
Technology
Platforms & Tooling
Planning machine learning on top of this foundation? See our AI Engineering services.
Warehouses & lakehouses
- Snowflake
- Databricks
- BigQuery
- Redshift
- Synapse
Processing
- Apache Spark
- dbt
- Flink
- Python
- SQL
Streaming
- Kafka
- Kinesis
- Pub/Sub
- Event Hubs
Orchestration & quality
- Airflow
- Dagster
- Great Expectations
- Soda
BI
- Power BI
- Tableau
- Looker
- Superset
Cloud
- AWS
- Microsoft Azure
- Google Cloud Platform
Approach
How We Engage
- Step 01
Audit
We trace your current data flows, quality gaps and reporting pain, and produce a prioritized remediation plan.
- Step 02
Design
Target architecture, data model and governance approach, sized to your team and budget.
- Step 03
Build
Incremental delivery, starting with the highest-value domain, so value lands before the full platform is finished.
- Step 04
Sustain
Monitoring, quality enforcement, cost tuning and enablement so your team can own it.
FAQ
Questions about this service
We provide data pipeline development, ETL/ELT solutions, data lake implementation, data warehousing, big data engineering, and cloud data platform services.
Yes. We help organizations modernize legacy databases and analytics platforms into scalable cloud-native data ecosystems.
We provide business intelligence, dashboard development, real-time analytics, predictive analytics, operational reporting, and advanced data visualization solutions.
We work with AWS, Azure, Google Cloud, Snowflake, Databricks, Redshift, BigQuery, Synapse, and other modern data platforms.
Yes. We develop real-time and streaming data solutions for operational intelligence, IoT analytics, monitoring, and event-driven architectures.
Absolutely. We design and implement scalable enterprise data warehouses and centralized analytics platforms.
We implement validation frameworks, governance policies, data lineage, access controls, and monitoring systems to maintain high-quality and secure data environments.
Yes. We create interactive dashboards and reports using Power BI, Tableau, Looker, and other visualization platforms.
Yes. We integrate data from ERP systems, CRMs, APIs, IoT devices, cloud platforms, databases, and other third-party applications.
Start A Conversation
Spending more time reconciling numbers than acting on them?
Start with a data audit. We’ll map where the trust breaks down and what it takes to fix it.