Data Engineering

Build the foundation. Power every insight.

We design the pipelines, lakes and warehouses that collect, clean and serve your data, so analytics and AI run on information you can trust.

Overview

Data you can depend on

Every dashboard and every model is only as good as the data underneath it. We make that layer fast, governed and built to grow.

We ingest structured, semi-structured and unstructured data from across the business, transform it with tested, version-controlled code and store it in platforms like Snowflake, Databricks, Redshift, BigQuery or Synapse. Cloud, hybrid or on-premise, the architecture fits your landscape and your compliance needs.

Modernize Your Data Platform
What we deliver

Key elements of our data engineering

End-to-end data infrastructure, from first ingestion to analytics-ready tables.

01

Data Pipeline Development

Batch and real-time ETL/ELT pipelines on Spark, Airflow, Kafka and dbt, built for low latency.

02

Cloud Data Platforms

Data estates on AWS, Azure and Google Cloud, migrated cleanly and tuned for cost.

03

Data Lake & Warehouse Design

Lakes, warehouses and lakehouses on open formats like Parquet, Delta Lake and Iceberg.

04

Data Quality & Governance

Checks on accuracy and freshness, plus lineage and access policies aligned with GDPR and HIPAA.

05

Metadata & Cataloging

Searchable catalogs with DataHub, Apache Atlas or cloud-native tools showing ownership and lineage.

06

DataOps & Automation

CI/CD, testing and alerting for data code, so releases are fast, repeatable and production-grade.

Our approach

From source systems to trusted data

Each layer is designed, tested and documented before the next one builds on it.

Audit

Map data sources, volumes, quality issues and downstream needs.

Architect

Choose platform, storage formats and pipeline patterns.

Build

Develop ingestion, transformation and serving layers.

Govern

Add quality checks, lineage, cataloging and access controls.

Operate

Automate deployments, monitor pipelines and scale as data grows.

Business advantages

Why enterprises build data platforms with us

Clean, timely data that every team, report and model can rely on.

  • One reliable data foundation
  • Real-time and batch processing
  • Analytics- and AI-ready data
  • Lower storage and compute costs
  • Built-in data quality checks
  • Regulatory compliance support
  • Clear lineage and ownership
  • Faster data delivery
  • Scalable from terabytes to petabytes
  • Less manual data wrangling
Why I-Vintage

Data platforms built to scale

Engineering rigor and long-term thinking, so today's pipelines still hold up next year.

01

Modern tech stack

Spark, dbt, Snowflake, Delta Lake and Airflow for speed and scale.

02

Platform agnostic

Cloud-native, hybrid or on-premise, matched to your strategy.

03

Built for growth

Modular designs that handle terabytes to petabytes.

04

Ready for analytics & AI

Data flows straight into BI dashboards and ML models.

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