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Data services · ETL & pipelines

Data pipelines that just run.

ETL and ELT pipelines that move, transform and validate data between Salesforce, your ERP, SaaS tools and your warehouse, with orchestration, monitoring and quality checks built in.

Data engineers who build pipelines to be operated.
At a glance
ETL / ELT
Batch, incremental or streaming
Tested
Quality checks on every load
Monitored
Alerts before users notice
dbt
Airflow, MuleSoft, Informatica
Since 2017
10+ years of delivery
200+
Projects delivered
100+
Salesforce certifications
5
Regions served
The challenge

Moving data by hand does not scale.

Nightly CSV exports, fragile scripts and jobs nobody owns. When one breaks, you find out from a wrong number in a board report. Reliable pipelines are engineered, tested and monitored like any other production system.

✕
Manual exports and imports
Someone runs a CSV job every morning.
✕
Pipelines that fail silently
Broken loads only noticed when a report looks wrong.
✓
Automated, monitored data flow
Tested pipelines with orchestration, alerts and quality checks.
Sound familiar? If any of these ring true, let's map your data pipelines.
?

Someone exports CSV files and re-imports them every day or week.

?

Scheduled scripts break when a field is renamed and nobody notices.

?

Reports show different numbers depending on when data was loaded.

?

Loads take hours and overlap with business hours.

?

Nobody documents what each job does or who owns it.

?

You need near real-time data, but everything runs nightly.

What we do

Pipelines, from source to trusted table.

A single scheduled feed or a full ingestion platform, built on the right pattern (batch, incremental or streaming) for your volumes.

Pipeline Design

Source analysis, load patterns and target design for batch, incremental (CDC) and streaming data.

Transformation Logic

Tested, version-controlled transformations in dbt, SQL or Python, with business rules documented.

Scheduling & Orchestration

Airflow, cloud schedulers or managed tools that run jobs in the right order, with retries and dependencies.

Data Quality Checks

Validation on volumes, keys, nulls and business rules, so bad data is stopped before it reaches a report.

Salesforce Data Pipelines

Bulk API, Change Data Capture and Data Cloud ingestion built around Salesforce limits and data model.

Monitoring & Support

Dashboards, alerting and runbooks so failures are caught and fixed before anyone relies on stale data.

Our pipeline method

Engineered to run, not just to load.

01
01

Assess

Map sources, volumes, frequencies and the reports that depend on them.

02
02

Design

Choose ETL or ELT, batch or streaming, and define contracts and error handling.

03
03

Build

Version-controlled pipelines and transformations, reviewed and unit-tested.

04
04

Test & Harden

Volume, failure and recovery testing with quality checks on every load.

05
05

Operate

Monitoring, alerting and support to keep data flowing reliably.

What you get

Pipelines you can trust and maintain.

Pipeline Architecture

Documented sources, patterns, schedules and dependencies.

Tested Transformations

Version-controlled logic with tests and business rules written down.

Monitoring & Alerting

Dashboards and alerts that flag failures and late or bad data.

Runbooks & Handover

What to do when something fails, and training so your team can own it.

The iTech difference

Pipelines built to survive schema changes.

iTechCloud
Typical scripts
Build
Version-controlled
Ad hoc scripts
Loads
Incremental / CDC
Full reload nightly
Data quality
Checked every run
Found in reports
Failures
Retries + alerts
Silent
Ownership
Documented & handed over
One person knows
Pipeline packages

From one feed to a data platform.

Fixed-scope packages that automate your most painful data flows first, then scale into a governed ingestion platform.

Single Pipeline

Automate one critical feed

One source to one target
Transformation & mapping
Error handling
Go-live support
Talk to us
Popular

Pipeline Suite

Several business-critical flows

Everything in Single
Multiple sources
Orchestration & scheduling
Quality checks & alerting
Talk to us

Data Platform

Ingestion at scale

Everything in Suite
CDC & streaming
Reusable framework
Ongoing managed support
Talk to us
Why iTechCloud

Data engineers who think in operations.

Salesforce data experts

Bulk API, CDC and governor limits handled properly, not worked around.

Engineering discipline

Code review, testing and CI/CD for pipelines, like any production software.

Quality built in

Checks on every load, so issues are caught before they reach a dashboard.

Built to be operated

Monitoring, alerting and runbooks so pipelines stay healthy after launch.

Credentials

Certified where it counts.

100+
Certifications held
12
Certified architects
6
Cloud specialties
Select
Salesforce Partner
CSAT 4.9
Average engagement score
ISO 27001
Security certified
Tools we build with

Modern tooling, chosen for your stack.

Managed connectors, transformation frameworks and orchestrators, or native Salesforce tooling where that fits better.

dbt
Apache Airflow
MuleSoft
Informatica
Fivetran / Airbyte
AWS Glue / Azure Data Factory
Sources & targets

Data flows we build time and again.

A sample of the sources, targets and tools in the pipelines we build.

SF
Salesforce
CRM
DC
Salesforce Data Cloud
Customer data
SAP
SAP S/4HANA
ERP
NS
Oracle NetSuite
ERP / Finance
DY
Microsoft Dynamics
ERP / CRM
SN
Snowflake
Data warehouse
BQ
Google BigQuery
Data warehouse
DB
Databricks
Lakehouse
PG
PostgreSQL / MySQL
Database
MS
SQL Server
Database
DT
dbt
Transformation
AF
Apache Airflow
Orchestration
MS
MuleSoft
iPaaS
IN
Informatica
Data integration
FT
Fivetran
Ingestion
AD
Azure Data Factory
Orchestration
GL
AWS Glue
ETL service
KF
Kafka
Streaming
S3
AWS S3
Data lake
FT
SFTP & flat files
Legacy feeds
FAQ

ETL & pipelines, answered.

ETL transforms data before loading it; ELT loads raw data into a warehouse and transforms it there. Modern cloud warehouses usually favour ELT with dbt, while ETL still suits some operational and Salesforce-bound flows. We choose per pipeline.
Whatever the use case needs. Many reports are fine hourly or nightly; operational processes may need Change Data Capture or streaming. We design for the freshness the business actually requires, which keeps cost down.
We use the Bulk API for volume, CDC and Platform Events for change streams, incremental loads instead of full extracts, and scheduling that respects your org’s limits.
Jobs retry automatically where safe, and alerts reach the right people with context. Runbooks explain how to recover, and data quality checks stop bad loads before they reach reports.
Not always. Managed connectors save time for common SaaS sources; custom code or native tools are often better for complex logic or cost. We recommend the mix that fits your volume and budget.
Yes. We audit what runs today, document it, fix the fragile parts and migrate it onto a monitored, version-controlled framework in stages.

Let's automate your data flows.

Book a free pipeline workshop. We'll map your sources and design flows that run themselves.