Nearshore data engineering services
Senior LATAM engineers who build the pipelines your reporting and your models depend on, working your hours, at 30-50% below US rates.
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15+years delivering software
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100+senior engineers across LATAM
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6-8hdaily overlap with US teams
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6+Fortune 500 & global brands trust us
Senior data engineers who get the data where it needs to be
Analytics teams stall when the data arrives late, arrives wrong, or arrives in six incompatible shapes.
FusionHit is a data engineering company with senior engineers across Latin America who build and operate the layer underneath, on your hours.
\ Data engineering services we deliver
The plumbing that decides whether your analysts spend their week analyzing or reconciling.
Data pipeline development
Batch and streaming pipelines built as code, orchestrated and monitored, so a failed load raises an alert instead of surfacing in a meeting three days later.
Data integration
Sources connected and reconciled into one model, including the legacy systems and the spreadsheets nobody wants to admit are load-bearing.
Data warehouse development
Warehouses on Snowflake, BigQuery or Redshift, modeled for the questions your business asks rather than for the shape the source system happened to use.
Data lakes
Raw and curated storage layers for the data you are not ready to model yet, structured enough that it stays usable rather than becoming a swamp.
Big data development
Distributed processing on Spark and Kafka for volumes that stopped fitting in a database, tuned for cost per run as much as for speed.
Data governance
Ownership, access rules, lineage and cataloguing, so the answer to where a number came from takes a minute rather than a meeting.
A data product in production before a platform nobody uses
Data programs fail slowly and expensively, usually by building infrastructure for months before anyone gets an answer out of it. We work the other way around.
One use case first
The engagement starts with the question your business most needs answered and the pipeline that answers it, which puts something in front of users while the architecture is still cheap to change.
Architecture validated by real consumption
The platform grows around what people actually query, so you find out early whether the model holds up, rather than after everything has been built on top of it.
Quality checks inside the pipeline
Freshness, volume and schema tests run on every load, and the alert fires before somebody makes a decision on bad data.
Why US companies choose FusionHit for data engineering
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Senior engineering talent
Vetted nearshore engineers with production experience across industries and modern stacks.
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Real-time collaboration
Nearshore teams aligned with US time zones for synchronous planning, reviews, and delivery.
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Flexible engagement
Scale engineering capacity up or down as your roadmap and priorities evolve.
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Integrated partnership
We work as an extension of your engineering and product teams, not as a detached external vendor.
Data platforms carrying real reporting
Making 130,000 Financial Documents Searchable with AI
Challenge A financial operations team was spending 2–3 hours per search session manually navigating complex document repositories — scanned PDFs, spreadsheets,…
Modernization at Scale in a Distributed Commerce Platform
Challenge A large-scale engineering team managing dozens of repositories faced mounting technical debt: outdated runtimes, a fragmented CI pipeline spread across…
Architecture Documentation Reverse Engineering
Challenge Two core services had evolved organically, and their architecture had never been formally documented. The team was preparing for an…
Data work shaped by what your sector has to prove
Every industry has a number it has to defend, and the pipeline is where that number is made.
Fintech
Transaction and risk data modeled for reporting that a regulator will read line by line.
Healthcare
Clinical and claims data unified across systems, moved and stored on a HIPAA-aligned path.
SaaS
Product usage and billing data joined into the metrics your board asks about every quarter.
Logistics
Telemetry and shipment data landing continuously, at a cost per event that survives the volume.
Retail
Sales, inventory and loyalty data reconciled across channels, so one product has one number.
Manufacturing
Sensor and production data captured at the line and made usable above it.
Data technologies we work with
The platforms your data already lives on, and the tooling that moves it between them.
Warehouses
Lakehouse & big data
Orchestration & transformation
Databases
Cloud
Governance
Three ways to engage a data 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 assessment, build, documentation and handover.
How a data engineering engagement starts
FAQs about our data engineering services
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How much do data engineering services cost?
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What can we have working in the first 90 days?
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Can you work with the warehouse we already have?
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How do you handle data quality?
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Who owns the pipelines and the code?
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Can our analysts keep working while this happens?
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Do you also build the dashboards?
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How do you handle security and compliance?
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How fast can data engineers start?
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How much time zone overlap will we have?
Ready to make your data usable?
Tell us what your sources are and what your team cannot answer today, and we will show you the team and the first use case.
Trusted by leading teams
Rated by our clients
