---
title: 'Data-AI Architect at dLocal'
canonical: 'https://feeny.ai/job/data-ai-architect-dlocal-montevideo-bq6f1bxreq1c'
type: 'job'
last_seen: '2026-11-04'
---

# Data-AI Architect at dLocal

- **Company:** dLocal
- **Location:** Montevideo, Uruguay
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-21
- **Last confirmed live:** 2026-11-04
- **Apply:** https://jobs.lever.co/dlocal/9152099e-3a47-48f0-8ab2-c68728012a79

## Job description

Why Join dLocal?dLocal is the financial infrastructure powering global commerce in the world's fastest-growing markets. The biggest companies in the world trust us to unlock growth in 60+ countries across emerging markets—moving money where others see complexity. We don't just process payments; we are architects of payment ecosystems and partners in our customers' expansion. You'll work alongside 1,300+ teammates from 40+ nationalities and tackle global challenges from day one.

What’s the opportunity? We are looking for a Data Architect to provide the technical direction for dLocal’s data and analytics architecture. This role will shape a scalable, governed, and highly consumable data ecosystem across Data & AI and engineering—connecting domain-owned data products, real-time platforms, analytical workloads, machine-learning use cases, and business-facing data consumption. You will act as a senior technical reference for architecture decisions, translating business and product needs into pragmatic designs that balance scalability, reliability, latency, security, interoperability, developer experience, and total cost of ownership.

What will I be doing?

- Define and evolve enterprise data architectures, evaluate trade-offs, and recommend fit-for-purpose technology patterns across batch, streaming, lakehouse, warehouse, and operational use cases.

- Review and advise other architects on the data aspects of their RFCs, helping ensure consistency with enterprise data principles, governance standards, and architectural direction.

- Lead the adoption of data-mesh principles, including domain-oriented ownership, data as a product, federated computational governance, self-serve platform capabilities, discoverability, quality, and measurable data-product SLAs.

- Establish reference architectures and engineering standards for data products, pipelines, ingestion, storage, processing, orchestration, observability, lineage, security, and access management.

- Provide oversight on operational SLAs, including latency, cost, quality, freshness, reliability, and production performance.

- Design and govern streaming architectures using technologies such as Kafka, Kinesis, Flink, Spark Structured Streaming, and Databricks, supporting use cases from scheduled batch through sub-second real-time processing.

- Define reliable event-processing patterns, including schema and data contracts, schema registries, event-time processing, late-event handling, idempotency, deduplication, replay and reprocessing, dead-letter flows, and freshness SLAs.

- Shape semantic layers and enterprise ontologies that create consistent business meaning across domains, including canonical entities, metrics, dimensions, relationships, business definitions, metadata, lineage, and versioning.

- Establish patterns that allow semantic models to serve analytics, operational applications, machine learning, and AI use cases without creating duplicated or contradictory definitions.

- Guide the evolution of cloud data platforms and lakehouse capabilities, including Databricks, Unity Catalog, Delta/Iceberg tables, object storage, data warehouses, and BI consumption layers across AWS and GCP environments.

- Provide architectural direction for MLOps and feature-platform capabilities, including batch and online features, model-serving integrations, low-latency data paths, model/data lineage, monitoring, and governance.

- Lead or contribute to architecture RFCs, technical decisions, design reviews, migration plans, and implementation roadmaps; make complex trade-offs clear to both technical and non-technical stakeholders.

- Partner with domain teams to clarify ownership, data-product responsibilities, operational handover, quality accountability, access approval, and cross-domain consumption models.

- Define practical controls for data quality, observability, privacy, security, resilience, cost management, and production readiness.

- Take ownership of critical architectural issues, facilitate resolution across teams, and ensure decisions are followed through to implementation and operation.

- Act as a trusted advisor and technical mentor to data engineers, platform teams, data scientists, MLOps engineers, BI teams, and engineering leaders.

- Communicate a cohesive architectural vision while remaining pragmatic, adaptable, and close enough to implementation to validate that designs work in production.

What skills do I need?

- 8–10+ years of experience designing and operating scalable data architectures, preferably in complex enterprise or high-growth environments.

- Strong experience designing and implementing data-mesh architectures and operating models, including domain ownership, data products, federated governance, self-serve platforms, contracts, quality, and discoverability.

- Deep experience with streaming and event-driven architectures, including Kafka or Kinesis and one or more processing engines such as Flink or Spark Structured Streaming.

- Demonstrated ability to design for real-time and near-real-time workloads, including latency measurement, event-time semantics, late data, state, deduplication, idempotency, replay, and failure recovery.

- Strong knowledge of semantic layers, business ontologies, canonical data models, knowledge graphs or metadata models, metric definitions, and semantic governance.

- Expertise in data modeling, data lake and lakehouse patterns, warehouse design, data pipelines, data products, metadata, lineage, and data management technologies.

- Experience with cloud data platforms and services, particularly AWS and/or GCP; experience with Databricks, Unity Catalog, Delta Lake, Iceberg, or comparable technologies is valuable.

- Proficiency with relevant data and platform technologies such as Spark, Airflow, dbt, Kafka, Python, SQL, CI/CD, infrastructure-as-code, and observability tooling.

- Experience architecting or supporting MLOps, feature stores, online/offline data serving, or other low-latency machine-learning data systems.

- Ability to establish practical frameworks for data access, stewardship, governance, privacy, security, quality, and operational accountability.

- Strong understanding of reliability, scalability, performance, resilience, cost, and vendor lock-in trade-offs.

- Excellent stakeholder-management, communication, facilitation, and influencing skills, including the ability to balance delivery expectations and technical excellence.

- Comfortable managing risk, ambiguity, and conflict; able to make decisions and explain the reasoning behind them.

- Self-sufficient and proactive, with the judgment to know when to seek input and when to move forward.

What do we offer? Besides the tailored benefits we have for each country, dLocal will help you thrive and go that extra mile by offering you:

- Flexibility in how you work: We focus on impact and productivity over fixed hours. This means our teams have flexible schedules and, depending on your role and location, you will combine self‑managed focus time with moments of in‑person connection in our collaboration hubs.
- Fintech industry: work in a dynamic and ever-evolving environment, with plenty to build and boost your creativity.
- Referral bonus program: our internal talents are the best recruiters - refer someone ideal for a role and get rewarded.
- Work From Anywhere: Team members can work while traveling for up to 3 months every year.

What happens after you apply? Our Talent Acquisition team is invested in creating the best candidate experience possible, so don’t worry, you will definitely hear from us. We will review your CV and keep you posted by email at every step of the process!

Also, you can check out our webpage, Linkedin and Youtube for more about dLocal!

## About dLocal

## Company Overview
- **One-liner**: dLocal provides a cross-border payment platform that enables global merchants to accept payments and disburse payouts in emerging markets through a single API.
- **Entity Type**: Public (Nasdaq: DLO)
- **Headquarters**: Montevideo, Uruguay
- **Founded**: 2016
- **Founders**: Sebastián Kanovich (former CEO), Sergio Fogel, Andrés Bzurovski, and Federico Pfeifer

## Core Business
- **Primary industry/industries**: Financial technology (Fintech), Payment Infrastructure
- **Target customers**: B2B; global e-commerce merchants, digital platforms, marketplaces, and enterprises seeking to expand into emerging markets
- **Mission or purpose statement**: To close the payments innovation gap between international businesses and emerging economies.

## Products & Services
- **Payins**: Accept local payment methods (credit/debit cards, cash, bank transfers, digital wallets) across 60+ countries, with dynamic FX conversion, to boost conversion rates.
- **Payouts**: Disburse funds to local bank accounts, digital wallets, and other methods in emerging markets.
- **dLocal for Platforms**: A solution for global marketplaces to onboard users, accept, send, and split funds between multiple users across high-growth markets.
- **Defense Suite**: A comprehensive fraud management solution designed to minimize financial loss and build merchant reputation.
- **Direct Issuing**: Enables merchants to issue virtual and physical cards in local markets.

## Market Standing
- **Valuation/Market Cap**: As a public company, market cap fluctuates. As of early 2025, it was roughly in the $2-3 billion range (check latest figures).
- **Key Metric**: Processed **$41 billion** in payment volume in 2025. Annual revenue is publicly reported in SEC filings (10-K/10-Q), with recent reports showing strong growth.
- **Notable Investors/Partners**: Key investors include Alkeon Capital, General Atlantic, and others. Major merchants include global giants like Uber, Amazon, and Spotify.
- **Growth Signals**: Expanded to over 1,000 payment methods and operations in 44+ countries as of 2025; team has grown to over 1,200 employees; continues to expand into Africa, Asia, and Latin America.

## Competitive Advantages
- **Deep Local Expertise**: Has "boots on the ground" in every region where they process payments, offering superior compliance, KYC, and local regulatory knowledge.
- **Single API, Broad Coverage**: A single integration provides access to 1,000+ payment methods in 60+ countries, simplifying a highly complex landscape.
- **AI-Powered Smart Routing**: Uses AI to optimize transaction routing for higher conversion rates, with robust fallback and redundancy.
- **First-Mover Advantage**: Pioneer in the cross-border payments space for emerging markets, building a strong network effect with merchants and local partners.

## Strategic Focus
- **Geographic Expansion**: Continuing to expand payment coverage in Africa, Asia, and Latin America.
- **Product Innovation**: Enhancing the platform with AI-driven fraud prevention, smart routing, and new financial products like direct issuing.
- **Platform Economics**: Deepening relationships with large global merchants and expanding the "dLocal for Platforms" offering to capture marketplace and platform payment flows.

## Why Work Here
- **Culture ("dLocal Drive")**: The company seeks ambitious people who thrive in a fast-paced, high-adrenaline environment with a focus on making the "impossible happen."
- **Remote/Hybrid Policy**: Offers flexible schedules and a "Work From Anywhere" policy allowing employees to work from anywhere for up to 3 months per year. Many roles are hybrid (Buenos Aires, Montevideo, Sao Paulo, Madrid, London, etc.).
- **Global Team**: A diverse team of over 1,200 professionals from around the world, with a strong presence in Latin America, Africa, and Asia.
- **Benefits**: Includes a referral bonus program, learning & development tools, a social budget for team connection, and a focus on global talent with local expertise.
- **Growth Opportunity**: Working at a public company with a strong growth trajectory provides exposure to complex global challenges and career advancement in a high-impact fintech.

## Sources
1. [dlocal.com](https://www.dlocal.com/)
2. [dlocal.com - About Us](https://www.dlocal.com/company/about-us/)
3. [dlocal.com - Careers](https://www.dlocal.com/careers/)
4. [investor.dlocal.com](https://investor.dlocal.com/)
5. [jobs.lever.co/dlocal](https://jobs.lever.co/dlocal)

## Other roles at dLocal

- [Head of Commercial Partnerships](https://feeny.ai/job/head-of-commercial-partnerships-dlocal-madrid-gtzzes4mfexa) — Madrid, Spain
- [People Operations Specialist](https://feeny.ai/job/people-operations-specialist-dlocal-sao-paulo-dz9tmsrkkmsr) — São Paulo, Brazil
- [Staff Engineer, AI R&D](https://feeny.ai/job/staff-engineer-ai-r-d-dlocal-madrid-paazqad5aqam) — Madrid, Spain
- [Regulatory Compliance Officer (PQ'd)](https://feeny.ai/job/regulatory-compliance-officer-pq-d-dlocal-mosta-db1gny4zn5ta) — Mosta, Malta
- [Regulatory Compliance Assurance Specialist](https://feeny.ai/job/regulatory-compliance-assurance-specialist-dlocal-mosta-6ed2v391tbyx) — Mosta, Malta
- [FinOps Specialist](https://feeny.ai/job/finops-specialist-dlocal-madrid-t3c8tf9fhgww) — Madrid, Spain
- [Legal Counsel - Contracts](https://feeny.ai/job/legal-counsel-contracts-dlocal-montevideo-5mxbf1fxdn3f) — Montevideo, Uruguay
- [Staff AI Engineer - AI Labs](https://feeny.ai/job/staff-ai-engineer-ai-labs-dlocal-madrid-dv0sd7qtk1a2) — Madrid, Spain
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- [Technical Lead - Java](https://feeny.ai/job/technical-lead-java-dlocal-barcelona-y30nh79a3mfd) — Barcelona, Spain