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01 · Services · Data

Data Engineering at Petabyte Scale

Streaming ingestion, lakehouse architectures, and orchestration that handle 10TB+ daily — without flinching, without overspending.

Legacy batch systems can't keep up with real-time business decisions.
Cloud bills balloon when pipelines aren't engineered for cost.
Our Expertise
Strategy . Delivery . Outcomes

Built to move your data engineering at petabyte scale roadmap faster.

Our data engineering team has migrated petabytes from on-prem mainframes to modern lakehouses, designed CDC pipelines for global logistics platforms, and rebuilt analytics stacks for top-tier retailers. We optimize for cost, latency, and developer ergonomics — in that order.

0+
Years in cloud data
0+
Migrations delivered
0
Cloud platforms
0M
Daily ingestion
01Why This Matters

"Your data isn't the problem. The pipes carrying it are."

  • 01

    Legacy batch systems can't keep up with real-time business decisions.

  • 02

    Cloud bills balloon when pipelines aren't engineered for cost.

  • 03

    Data quality issues compound silently until reports collapse.

02What We Offer

Our Data Engineering at Petabyte Scale Practice.

01 / 04
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What We Offer

Kafka, Kinesis, Pub/Sub — real-time event pipelines with exactly-once semantics and replay.

KafkaKinesisFlink

Streaming Ingestion

◇
What We Offer

Delta Lake and Iceberg architectures on Databricks, Snowflake, BigQuery — open and cost-optimized.

DeltaIcebergHudi

Lakehouse Architectures

◈
What We Offer

Production-grade DAGs with retries, SLAs, lineage, and observability — built on Airflow, Dagster, or dbt.

AirflowDagsterdbt

Pipeline Orchestration

◉
What We Offer

Legacy-to-cloud, on-prem-to-lakehouse, and warehouse-to-warehouse migrations — with zero downtime.

AWS DMSFivetranCustom CDC

Migration & Modernization

03Expertise

Depth before width.

Our data engineering team has migrated petabytes from on-prem mainframes to modern lakehouses, designed CDC pipelines for global logistics platforms, and rebuilt analytics stacks for top-tier retailers. We optimize for cost, latency, and developer ergonomics — in that order.

0+
Years in cloud data
0+
Migrations delivered
0
Cloud platforms
0M
Daily ingestion
Teams work with us when they need measurable movement, not another deck of ideas.
04Technology Stack

Our Core Technology Stack

Cloud
AWSGCPAzureSnowflake
Processing
SparkDatabricksFlinkBeam
Orchestration
AirflowDagsterdbtPrefect
Streaming
KafkaKinesisPub/SubConfluent
05Approach

How We Work.

  1. 01

    Architecture Audit

    We map your existing data flows, identify bottlenecks and cost leaks, and define the target-state architecture.

  2. 02

    Lakehouse Design

    Layered medallion architecture, partitioning strategy, schema governance — designed for the next 5 years.

  3. 03

    Pipeline Build & Migration

    Incremental migration with parallel run, data reconciliation, and zero downtime to production analytics.

  4. 04

    Optimize & Operate

    Cost monitoring, query optimization, SLA dashboards, and on-call runbooks — handed off cleanly.

System Flow
Kafka / Kinesis
S3 / GCS
REST APIs
Databases
Ingestion Layer
CDC · Streaming
Apache Spark
Databricks / Glue
dbt Transforms
Lakehouse Layer
Snowflake · BigQuery · Redshift
BI Tools
ML Models
Dashboards
Data APIs
High-level architecture
Logistics · Data Engineering

Petabyte ingestion for a global 3PL

14× faster pipelines · 62% cloud cost cut · Q4 2024

Top-5 global 3PL provider
Read Case Study
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