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Nearshore data integration services

Nearshore data integration services

Senior LATAM engineers who connect your systems and prove the numbers match on the other side, working your hours, at 30-50% below US rates.

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Applebees
KPMG
Mastercard
Microsoft
NetJets
Toyota
  • 18+
    years delivering software
  • 150+
    senior engineers across LATAM
  • 6-8h
    daily overlap with US teams
  • 6+
    Fortune 500 & global brands trust us
Who we are

Senior data engineers who connect systems that were never meant to talk

Data teams come to us when the reporting depends on four systems, two of them are older than the analysts, and every number has to be checked by hand before anyone will present it.

FusionHit builds the pipelines in between, with senior engineers across Latin America working inside your stack and your sprint cadence.

FusionHit senior nearshore data engineers connecting client systems with a US team \
WHAT WE DELIVER

Data integration services we deliver

Integration is not one job. Which of these you need depends on how fresh the data has to be and what you are allowed to touch at the source.

ETL and ELT pipelines

Batch pipelines built either way round: transformed before loading when the target is strict, or loaded raw and transformed in the warehouse when it is not. We choose per source rather than by house style.

Streaming and change data capture

Continuous integration for the data that cannot wait for tonight's run, reading changes off the source log rather than polling it and slowing it down.

API and application integration

Your SaaS platforms, ERP and CRM connected through their APIs, with rate limits, retries and pagination handled so the sync does not quietly stop on a Tuesday.

Cloud data migration

Data moved into Snowflake, Databricks, BigQuery or Redshift with reconciliation at both ends, so you can compare before you switch anyone over.

Data quality and validation

Rules that check the data on the way through rather than after someone spots a wrong figure in a board deck, with the failures routed somewhere a person will see them.

Pipeline monitoring and support

The pipelines kept running after they are built: freshness alerts, schema change detection, failed-run triage and the backfills nobody wants to do at 7am.

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TRUST

How you know the numbers moved correctly

Every provider on this search describes moving data. None of them says what happens when it moves wrongly, which is the part that costs you a quarter of bad reporting before anyone notices.

Reconciled at both ends

Row counts, sums and control totals compared between source and target on every run, not spot-checked at go-live. If a load is short by 400 rows you find out from us, not from a director looking at a dashboard.

Pipelines that fail loudly

A source that adds a column, renames a field or changes a type breaks the run on purpose rather than passing nulls downstream. Silent success on wrong data is the worst outcome available and it is the default in most pipelines.

Lineage you can follow back

Every field in the warehouse traceable to the system and the transformation it came from. When someone asks why the number changed, the answer takes minutes and comes with evidence.

Why FusionHit

Why US companies choose FusionHit for data integration

  • Senior engineering talent

    Vetted nearshore engineers with production experience across industries and modern stacks.

  • Real-time collaboration

    Nearshore teams aligned with US time zones for synchronous planning, reviews, and delivery.

  • Flexible engagement

    Scale engineering capacity up or down as your roadmap and priorities evolve.

  • Integrated partnership

    We work as an extension of your engineering and product teams, not as a detached external vendor.

FusionHit senior nearshore engineers working with a US client team
CASE STUDIES

Systems we connected and what it unblocked

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Your reporting can stop being a manual job.

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INDUSTRIES

Integration under the constraints your industry works with

What you are allowed to move, and how fresh it has to be, is decided by your sector rather than by the architecture.

Fintech

Transaction data consolidated with the audit trail and the retention rules your examiners will ask about.

Healthcare

Clinical and claims systems connected under HIPAA, with PHI masked everywhere it does not need to be readable.

SaaS

Product, billing and support data joined per tenant so the metrics your board sees agree with the invoices.

Logistics

Telemetry and dispatch data integrated at the speed operations actually decide, not overnight.

Retail

Point of sale, e-commerce and inventory reconciled across channels so the stock number means the same thing everywhere.

Manufacturing

Plant-floor and equipment data brought into the warehouse alongside the systems that plan against it.

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TECHNOLOGY EXPERTISE

Integration tools and platforms we work with

The managed connectors where they earn their cost, and code where they do not.

Orchestration & transformation

Managed connectors

Streaming & CDC

Cloud ETL

Warehouses

Cloud

HOW WE ENGAGE

Three ways to add data engineers to your team

Staff augmentation

Senior data engineers added to your existing team, under your direction, in days rather than months.

Dedicated development teams

A data team working only on your platform, sprint after sprint, while you set the priorities.

Full project outsourcing

You hand over the scope and we deliver it under our management, covering discovery, build, validation and handover.

Need the dashboards on top?

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OUR PROCESS

How a data integration engagement starts

01

Discovery call

Your sources, your targets, and how fresh the data has to be (30 minutes).

02

Source assessment

What each system will actually give us, what it will not, and where the surprises are.

03

Interviews

You meet and approve every engineer.

04

Sprint delivery

Pipelines shipped incrementally, reconciled and monitored from the first one.

FAQ

FAQs about our data integration services

01

How much do data integration services cost?
Senior nearshore rates run 30-50% below equivalent US salaries and consultancy fees. What a project costs depends on how many sources are involved, how cooperative each one is, and whether you need the pipelines maintained afterwards. You get a line-item estimate on the first call, with no recruiting fees and no hidden overhead.
02

ETL or ELT, which one do we need?
Usually ELT if your target is a modern cloud warehouse, because transforming there is cheaper and easier to change later. ETL still wins when the target is strict about what it accepts, when the data has to be masked before it lands, or when you are moving far more than you will keep. We decide per source, not per project.
03

Can you integrate a system that has no API?
Usually. Database replication, log-based change capture, file drops and scheduled exports all work, and one of them is normally available even on software from the nineties. What we will not do is screen-scrape a system and call it an integration, because that breaks the first time someone moves a button.
04

How do we know the data is complete and correct?
Reconciliation on every run: row counts, sums and control totals compared between source and target, with the result visible to you rather than in our logs. Discrepancies raise an alert before anyone builds a report on them.
05

What happens when a source system changes?
The pipeline fails on purpose. Schema changes, renamed fields and type changes stop the run and notify us rather than passing nulls into the warehouse. We would rather you have yesterday's data and know it than today's data and not.
06

Can you work with our existing pipelines?
Yes, and it is a common way we start. We map what is actually running against what is documented, fix what is silently broken, and take over the maintenance. Inherited pipelines are usually where the reconciliation gaps turn up.
07

Which tools do you build with?
Airflow and dbt for orchestration and transformation, Fivetran or Airbyte for the connectors where a managed connector is cheaper than maintaining one, Kafka or CDC for streaming, and Azure Data Factory or AWS Glue where the estate is already committed. If you already run a stack, we work in it.
08

Do you handle real-time, or only scheduled loads?
Both. Most reporting does not need real-time and paying for it is a common mistake. When it genuinely matters, whether that is fraud checks, inventory or dispatch, we build change data capture rather than shortening the batch interval until the source falls over.
09

How do you handle sensitive data during integration?
Masking or tokenization before the data leaves its source system where the classification requires it, encryption in transit and at rest, and least-privilege credentials issued by you. For HIPAA, PCI DSS and SOC 2 scope we keep the evidence as we go rather than reconstructing it at audit time.
10

Who owns the pipelines?
You do. Code lives in your repositories, orchestration runs in your accounts, and the contract assigns all intellectual property to you. Nothing depends on a platform of ours, so if the engagement ends your team runs the pipelines the next morning.
11

How fast can data engineers start?
We present matched profiles within days, you interview and approve them, and most engineers onboard in under 2 weeks.
12

How much time zone overlap will we have?
Our engineers work across Latin America on US Central and Eastern time, which gives 6-8 hours of daily overlap. Integration work depends on it more than most, because the answer about what a field means usually lives with someone on your side.

Ready to stop checking the numbers by hand?

Tell us which systems have to talk to each other and what breaks when they do not, and we will show you the team that can connect them.

Trusted by leading teams

  • Mastercard
  • NetJets
  • KPMG
  • Applebees

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