AutomateNexus

Service / Data Engineering

Data that flows automatically.

Data pipeline services and ETL consulting for growing companies. We eliminate data silos, automate manual reporting, and connect your systems to Power BI and Tableau — delivering actionable insights, not just raw data.

SNOWFLAKE · BIGQUERY · DBT · AIRBYTE

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What it looks like running.

Not a dashboard login we control —
an instance you own.

LIVEScheduleAIRBYTE SYNCTransformDBT BUILDExtractSOURCE INGESTSnowflakeLOAD + TESTNotifyFRESHNESS OKEXECUTIONS · TODAY05:30:52sync #1,204 → 2.1M rows05:25:31sync #1,203 → schema drift05:18:09sync #1,202 → tests passed/ SELF-HOSTED · YOUR SERVER · YOUR KEYS

Data Engineeringon self-hosted n8n — the kind of build that ships in week one.

0

MANUAL EXPORTS AND COPY-PASTE REPORTS

<1S

QUERY TIMES AT WAREHOUSE SCALE

24/7

PIPELINES WITH MONITORING AND LINEAGE

What you get

What's in the build

One-time fee. Documented. Owned by you.

ETL Pipeline Development

01

Automated pipelines that extract, transform, and load from any source — with fault tolerance, monitoring, and lineage tracking built in.

Data Warehouse Implementation

02

Dimensional modeling and optimized query patterns on Snowflake, BigQuery, or Databricks. Sub-second analytics at any scale.

System Integration

03

CRM to ERP to marketing platforms connected into unified analytics — the silos that forced manual reporting, dissolved.

Real-Time Analytics

04

Dashboards with sub-second data freshness, instant alerts, and operational intelligence — decisions made on now, not last month.

Data Quality Automation

05

Automated testing, lineage tracking, and governance frameworks. Data your team trusts enough to act on.

Cloud Migration

06

Legacy systems moved to cloud warehouses with zero-downtime strategies, validation, and performance optimization.

Use cases

Where it earns its keep

E-Commerce & Retail

01

Unified customer data, real-time inventory, and omnichannel analytics pipelines feeding recommendation and pricing decisions.

SaaS & Technology

02

Product analytics pipelines, usage metering, multi-tenant data isolation, and self-service reporting infrastructure.

Financial Services

03

Transaction pipelines, regulatory reporting, and fraud-detection data flows with the audit trails compliance demands.

Healthcare

04

HIPAA-compliant data lakes, patient data integration, and population health pipelines on infrastructure you control.

Manufacturing & IoT

05

Sensor ingestion at scale, predictive maintenance pipelines, and supply chain visibility from plant floor to dashboard.

Five phases. Thirty days to live.

Our process →

01

Discover

Ops audit, process maps, ROI ranking.

02

Design

Architecture and tool picks — approved first.

03

Build

Constructed and tested against every edge case.

04

Launch

Deployment, training, real adoption.

05

Optimize

Monitoring, monthly reports, new wins.

Questions

Data Engineering — FAQ

What problem does data engineering solve for an SMB?

Data silos and manual reporting. When CRM, accounting, and operations data live apart, someone spends hours exporting and reconciling spreadsheets. Pipelines make data flow automatically into one warehouse your BI tools read directly.

Snowflake, BigQuery, or Databricks?

Depends on workload, team, and budget — and we are vendor-neutral. BigQuery wins for Google-stack shops and bursty workloads, Snowflake for governed multi-source analytics, Databricks where ML pipelines dominate. We model costs for your actual usage before recommending.

Is this affordable for a growing company?

Yes — modern tooling collapsed the cost. A right-sized stack with Airbyte, dbt, and a cloud warehouse delivers what required a data team five years ago. A typical build is $7,500 one time, plus your cloud usage.

How do you keep pipelines from silently breaking?

Automated testing, freshness checks, lineage tracking, and alerting on every pipeline. Failures notify a human with context — the dashboard never quietly shows last Tuesday's numbers.

How fast until data is flowing?

First pipelines live in 30 days for most builds — sources connected, warehouse modeled, BI tools reading from it. We follow Discover, Design, Build, Launch, Optimize.

Where we go from here

Start with a call.

Thirty minutes, no pitch deck. We map your operations, find the friction, and show you where automation actually earns its keep. If there's no fit, we'll say so.

No subscription.

No lock-in.

No surprise invoices.

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