Data Engineering

Reliable data platforms for reporting, analytics, and machine learning—built with scalable pipelines and solid governance.

What’s Included

  • Batch and streaming pipelines (ETL/ELT)
  • Data modeling and warehousing (Lake/Lakehouse)
  • Workflow orchestration (Airflow, Dagster, etc.)
  • Event streaming (Kafka, Pub/Sub)
  • Quality checks, lineage, and governance
  • BI integrations and semantic layers
  • Cost management and performance tuning

Our Process

  1. 1

    Discovery

    Goals, constraints, and success metrics

  2. 2

    Plan

    Roadmap, milestones, and architecture

  3. 3

    Build

    Iterative development with demos

  4. 4

    Launch

    Hardening, rollout, and handover

  5. 5

    Evolve

    Monitoring and continuous improvements

Start a Data Engineering project