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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.
Arocom builds the data foundation that fixes it — reliable pipelines, well-modelled warehouses and lakehouses, and analytics your teams actually rely on. We work across AWS, Azure, Google Cloud, Snowflake and Databricks, with data quality, lineage and governance engineered in rather than promised later.

Our Data Engineering Services:

Data Strategy & Governance

  • Data maturity assessment
  • Target data architecture
  • Governance operating model and ownership
  • Data catalogue and lineage
  • Access control and privacy compliance
  • Metric definitions and semantic standards
01

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
02

Real-Time & Streaming Data

  • Evenat streaming architecture
  • Streaming ingestion and processing
  • Event-driven and CDC pipelines
  • IoT and telemetry data processing
  • Operational and near-real-time dashboards
03

Business Intelligence & Analytics

  • Semantic layer and metric modelling
  • Interactive dashboard development
  • Self-service analytics enablement
  • Operational and regulatory reporting
  • Exploratory data analysis
  • Embedded analytics
04

Data Warehouse & Lakehouse Engineering

  • Dimensional and data vault modelling
  • Cloud data warehouse implementation
  • Data lake and lakehouse architecture
  • Medallion layer design
  • Partitioning, clustering and query tuning
  • Storage cost optimisation
05

Data Quality, Migration & Modernisation

  • Automated data quality and validation frameworks
  • Legacy warehouse and database migration
  • On-premises to cloud modernisation
  • Reconciliation and parallel-run validation
  • Master data management
  • Performance and cost optimisation
06

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.

Modelled 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.

Platforms & Tooling

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

Planning machine learning on top of this foundation? See our AI Engineering services

How We Engage

01

Audit
We trace your current data flows, quality gaps and reporting pain, and produce a prioritised remediation plan.

02

Design
Target architecture, data model and governance approach, sized to your team and budget.

03

Build
Incremental delivery, starting with the highest-value domain, so value lands before the full platform is finished..

04

Sustain
Monitoring, quality enforcement, cost tuning and enablement so your team can own it.

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.

Questions about 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.