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Data Engineering Services
We recruit, hire, and retain your data engineering professionals in Mexico. You manage the work.
Your VP of Engineering, Head of Data, or Director of Analytics sets priorities, reviews deliverables, and runs the team directly. We build data engineering services around your leadership, not ours.
Data Engineers
We place trained data engineers who keep your warehouse loaded, your pipelines running, and your transformation logic clean. They report directly to your engineering leadership and operate in your sprint cadence from day one.
Analytics Engineers
We recruit analytics engineers who own the layer between your warehouse and your dashboards. dbt models, transformation logic, and clean datasets your analysts and BI tools can trust. They report directly to your Head of Data.
Data Platform Engineers
We source data platform engineers who own the foundation your data team takes for granted. Orchestration, compute, storage, access controls. When this layer is solid, your data engineers ship pipelines instead of firefighting infrastructure.
Streaming & Real-Time Data Engineers
We hire engineers who build and maintain real-time data pipelines using Kafka, Flink, or Spark Streaming. They handle event ingestion, stream processing, and low-latency delivery to your analytics and operational systems.
ML Data / Feature Engineers
We place data engineers who own the data side of your ML workflows. Feature pipelines, training datasets, and the infrastructure that gets clean data to your models on time. They work alongside your ML engineers under your data or ML platform lead.
Data Leads
We source senior data engineering leads who own architecture decisions, code review standards, and team coordination. They manage your nearshore data team directly under your VP of Engineering or Director of Data.
Active data engineering teams in fintech, healthtech, SaaS, and enterprise data platforms
English and Spanish native data engineers who join your standups and design reviews
First shortlist in 5-7 business days, your team is fully operational in 30 days
SOC 2 in progress, controlled data access and IP protection on every engagement
Across our key nearshore engineering partnerships
Open data engineering roles do not just slow your pipelines down. They stall product decisions, delay analytics delivery, and force your senior engineers to own data work that should not be theirs.
Data Engineering Talent Is Expensive and Slow to Hire Domestically
A senior data engineer costs six figures fully loaded in the U.S. Takes 3-4 months to fill. And they might leave in a year. Meanwhile, your data pipelines fall behind, your analytics team waits on clean data, and your roadmap slips.
Your Senior Engineers Are Maintaining Pipelines Instead of Building
When data engineering seats sit empty, the work does not disappear. It becomes the responsibility of your backend and platform engineers, who end up writing transformation logic, debugging ETL jobs, and firefighting data quality issues instead of shipping product. You are paying senior engineering rates for data engineering work.
Offshore Data Teams Break Your Data Review Cadence
12-hour time difference. Async-only pipeline reviews. Data incidents that surface after your morning standup. Offshore data engineering teams cannot participate in your architecture reviews, respond to same-day production incidents, or attend your data planning sessions. Your analytics team cannot wait for a timezone.
Bad Data Costs More Than Missing Data
When pipelines break silently, your analytics team makes decisions on stale or incorrect data. Reports contradict each other. Dashboards show numbers no one trusts. And the cost of tracing a bad data point back to its source is always higher than building the pipeline right the first time.
Every Tool You Add Creates Integration Debt Your Team Cannot Clear
Every new SaaS platform, data source, or internal system your business adopts needs a pipeline. Without dedicated data engineering capacity, your ingestion backlog grows faster than your team can build. The gap between what your data could tell you and what it actually tells you widens every quarter.
Lose one data engineer a year. That is 90 days to backfill, 60 days to ramp, and five months of stale pipelines your analytics team works around. What is that costing your reporting accuracy?
Our name comes from "amalgamate." We unite U.S. companies and Latin American engineering talent into one codebase, one data platform, one team. Not two disconnected pipeline cycles. Not a vendor relationship. One team.
Other providers stop at placement. Amalga handles what makes nearshore data engineering sustainable for U.S. engineering organizations: recruiting, vetting, onboarding, HR, and retention.
Your data engineers report to your Head of Data or VP of Engineering, join your daily standups, commit to your pipeline roadmap, and operate in your tools from day one. We handle everything behind the scenes (recruiting, payroll, benefits, and retention) so your engineering leadership only manages the data work.
Your engineering managers run the work. Amalga keeps the team stable. Our leadership team comes from General Electric, Bloomberg, Concentrix, Teleperformance, and Apollo Global Management. We have built engineering teams at scale before. We will build yours next.
10
Engineers
in 5 Months for One Client
Under
3 Months
to Full Sprint Parity
40-50%
Cost Savings vs. U.S.
100%
Retention
First 6 Months (Key Accounts)
97.8%
Annual Employee Retention
Our financial services client went from zero nearshore infrastructure to a 10-person engineering team in 5 months, with plans to scale to 20+ engineers by mid-2026. Full sprint parity with U.S. teams in under three months. Industry IT services attrition in offshore markets commonly runs 15-22% annually. Across our active nearshore engineering partnerships, we run well below that.
You have probably weighed nearshore vs. offshore before. Here is what actually changes when you go nearshore with Amalga for data engineering.
Not sure? Talk to us. We will help you figure out the right model.
Data engineering services work best when your team operates in your time zone. Monterrey and Mexico City offer direct flights from all major U.S. cities, which means real oversight, architecture reviews that actually happen live, and same-day site visits when you need them.
Houston
1 hr
Monterrey
Dallas
1.5 hrs
Monterrey
Miami
3 hrs
Monterrey
Los Angeles
3.5 hrs
Mexico City
Chicago
4 hrs
Mexico City
Compare that to 15+ hours to Manila or Bangalore. Offshore data teams run pipeline jobs and open incidents after your entire engineering team has already signed off for the day.
Same-day site visits. Real-time incident response. No jet lag. Your data engineering team works when you work.
Top Universities
Tec de Monterrey, UNAM, ITAM
55,000+ Tech Talent
Monterrey + Mexico City
Culturally Fluent
No communication gaps or rework cycles
Stable & Secure
ISO 27001 certified facilities
How Amalga built a nearshore engineering team for a financial services client running a compliance-heavy trading platform.
The Challenge
The Solution
The Results
Under 3 months
100% in the first 6 months
10 Engineers, Scaling to 25
Director of Engineering Global Technology Consultancy
*Results vary by engagement. This case study reflects one client's experience.
Want Us to Manage the Data Operation?
All of our current data engineering engagements are client-managed. If you want Amalga to own data delivery outcomes (managing your pipeline SLAs, data quality standards, and delivery cadence end to end), we can do that too.
Talk to Us About Managed Data Engineering Services →We do not ask you to change your data infrastructure. Your nearshore data engineers work in your warehouse, your orchestration layer, and your transformation framework from day one.
And many more. AWS, GCP, Azure, Terraform, Docker. If your team builds on it, we can work on it.
Book a Discovery Call
"The nearshore hub became a true extension of our engineering culture. Amalga’s execution was flawless."
"Amalga did not just fill seats. They understood our culture, our standards, and our urgency. The engineers they placed have become some of our most valuable contributors."
"Amalga's Mexico playbook took us from strategy to a fully functioning nearshore team in months, not years."
We provide client-managed data engineering teams. You direct the pipeline roadmap, architecture decisions, and sprint priorities. We recruit, onboard, and support the team so you get stable data engineering capacity and institutional knowledge continuity. We do not manage your data operations as a service, though if you want that model, we offer it as well.
data engineering servicesWe support data engineers, analytics engineers, data platform engineers, streaming data specialists, ML feature engineers, and data leads. We staff individual contributors or full data pods that embed directly into your existing engineering organization. For larger data teams, you get a data lead for every 5-6 engineers.
data engineering solutionsOur data engineers work across the modern data stack. Warehouse experience covers Snowflake, BigQuery, Redshift, and Databricks. Transformation and modeling runs on dbt and SQL. Orchestration covers Airflow, Dagster, and Prefect. Streaming covers Kafka and Spark Streaming. Python is standard across all data roles. We also support cloud-native infrastructure on AWS, GCP, and Azure. We can administer your own technical assessments before hiring, and we encourage it.
data science engineering servicesOur data engineering teams in Monterrey and Mexico City operate on Central Time, which overlaps fully with U.S. business hours. Your data engineers attend your architecture reviews, join sprint planning and retrospectives, and respond to pipeline incidents in real time. They are reachable on Slack or Teams the same way any local hire would be, with no overnight incident queue, no async pipeline review cycle, and no communication gap between your data and product teams.
big data engineering servicesWe are ISO 27001 certified, with SOC 2 certification in progress. You own the pipelines, the data models, and all work products, full stop. NDAs, role-based access controls, and secure environments using VPN or VDI are standard on every engagement. Your IT team provisions access directly and retains full control over warehouse, repository, and environment permissions.
data engineering solutionsWe handle replacement recruiting immediately using the same role profile and technical requirements. Our 100% retention rate in the first 6 months across active engineering engagements reflects how seriously we take stability. When turnover does happen, we manage the entire backfill process. Same vetting depth, same technical assessments, same onboarding.
data engineering servicesOur data engineering model is client-managed. Your Head of Data, VP of Engineering, or Director of Analytics directs pipeline priorities, architecture standards, and delivery cadence. We recruit, hire, onboard, and retain the talent. We handle HR, payroll, benefits, equipment, and workspace. Your engineering leadership manages the data work. If you want us to own data delivery outcomes and manage the operation end to end, we offer that model as well.
data engineering solutionsWe typically present qualified data engineering candidates to your hiring manager within 5-7 business days from the start of our engagement. From there, ramp time depends on your interview process, system access, and internal onboarding. Our financial services client had a 10-person engineering team (including data and platform engineers) deployed and operating at full sprint parity in under 5 months.
data science engineering servicesWe recruit across Mexico’s top engineering talent hubs, with a focus on Monterrey and Mexico City and graduates from universities including Tec de Monterrey, UNAM, and ITAM. Every candidate goes through technical screening specific to the data engineering function: pipeline design, warehouse modeling, transformation logic, or orchestration architecture, depending on the role. Candidates are assessed at CEFR B2-C1 English proficiency. We can also administer your own technical challenges. You approve every hire before they start.
big data engineering servicesYou pay a flat monthly rate per data engineer that covers everything: their fully loaded compensation plus our recruiting, HR, and infrastructure support. No per-pipeline pricing, no data SLA fees, no hidden overhead. Most clients see 40-50% savings compared to equivalent U.S. fully loaded data engineering costs.
data engineering solutionsTell us what you are building and where your data engineering gaps are.
We will come back with a plan that fits your stack, your roadmap, and your timeline.
