ABOUT THE ROLE

As a Data Engineer on the Data Platform team, you'll help design, build, and evolve the data infrastructure that powers analytics,

AI, and machine learning across VTEX. This is a hands-on, mid-level role: you'll own features end-to-end — from ingestion and

processing to storage and consumption — taking on problems that come with real ambiguity, and delivering them with growing

independence.

We're not looking for someone who arrives knowing everything. We're looking for someone with a strong engineering foundation and a

high ceiling: a fast learner with sharp problem-solving instincts who is energized by a data platform going through a deep

transformation of its architecture and the way it's built.

HOW WE WORK

The way we build has changed completely in the last year, and this role is defined by it. On this team, you don't measure yourself

by lines of code written — you measure yourself by the value and quality of what you ship. AI tools are part of every step of our

work: we direct them, review their output critically, and are accountable for the result.

That makes two things essential:

Leveraging AI to scale your impact. We expect you to use AI extensively and well — designing workflows where agents handle the

"known-knowns" (standard ETL, repetitive modeling) so your judgment goes to the hard, ambiguous problems. The goal is genuine

leverage: producing at a level that simply wasn't possible a year ago.

Clarity as a contract. The quality of your written word is the quality of your AI output. If you can't describe a

transformation clearly in a spec or doc, the code isn't ready to be written — by you or an agent. Strong technical writing and

spec-driven thinking aren't "nice to have" here; they're how the work gets done and how it scales to teammates and agents.

ABOUT THE TEAM

Data Platform is the team inside VTEX's Data & Analytics org that builds the foundation the rest of the company's data products

are built on. We're in the middle of a deep transformation: migrating from a Redshift-centric warehouse to a multi-engine Data

Lakehouse on Apache Iceberg, moving our infrastructure to EKS, and re-architecting ingestion for scale and cost. We run a lot of

initiatives in parallel, with high autonomy and a high quality bar.

You won't be siloed on one thing. You'll typically own at least one larger initiative while moving smaller improvements forward

alongside it. Depending on where you fit best, your work could span:

Data ingestion — migrating high-volume pipelines from Kinesis/Firehose to our new Kafka/AutoMQ-on-EKS stack.
Lakehouse migration & evolution — moving workloads onto Iceberg, Spark (EMR-on-EKS) processing, and new maintenance and

consumption tooling.

Platform infrastructure — Kubernetes/EKS, compute efficiency, reliability.
Query & consumption — engines like Trino, Cube, DuckDB, and Athena, and smart routing across them.
Platform tech debt, observability, and engineering-process improvements that keep the platform fast, reliable, and

cost-efficient.

You'll also have the opportunity to join the team's on-call rotation, helping keep a platform that ingests billions of events a

day healthy.

WHO YOU ARE

You think like a platform builder. You're motivated by designing the architecture, services, and capabilities that other teams,

products, and AI agents build on top of — not just by shipping a single pipeline. You care about the foundation as a product.

You can own a piece of the platform from design through to production with minimal supervision, taking on problems that carry

real ambiguity.

You're comfortable with modern data architectures — data warehouses, data lakes, and data lakehouses — and understand the

trade-offs that shape a platform others depend on.

You understand what makes a platform genuinely usable for its consumers: clean data modeling, well-designed data services and

APIs, reliability, and performance at scale (relational and/or NoSQL).

You're proficient in Python and its data-processing ecosystem, SQL, and you produce work that is idempotent, reproducible, and

documented — whether you wrote it or an agent did.

You've worked on a cloud data platform (AWS preferred; GCP/Azure welcome) and understand the realities of large datasets and

performance optimization.

You have a data-driven mindset. You define how the impact of your work will be measured before you build it, and you validate

outcomes against real-world results rather than assuming success.

You're proficient with AI assistants and code-generation tools, and you design solutions that thoughtfully consider when and

how AI should be used to enhance value delivery — directing, reviewing, and critiquing AI-generated work rather than just

accepting it.

You communicate clearly in writing — specs, docs, and design notes that other people (and agents) can act on — and you

collaborate well across engineering and non-engineering peers.

NICE TO HAVE

Real-time / streaming data processing (Kafka, AWS Kinesis, Flink).
Containerization and orchestration (Docker, Kubernetes/EKS).
Infrastructure-as-code (Terraform, CDK, CloudFormation).
Distributed processing with Spark.
Open table formats (Apache Iceberg, Delta, Hudi).
Data governance and security best practices (e.g., access control, multi-tenant isolation).
Building and deploying data APIs.

Title note: We hire for potential and fit, not just title. Data Engineer is the most direct match, but if you come from an

Analytics Engineering, Data Architecture, or Platform/SRE background with a strong data focus, you're welcome to join the process.

---------------------------------------------------------------------------------------------------------------------------------

ABOUT VTEX

VTEX (NYSE: VTEX) is the composable and complete commerce platform that delivers more efficiency and less maintenance to

organizations seeking to make smarter IT investments and modernize their tech stack. Through our pragmatic composability approach,

we empower brands, distributors, and retailers with unparalleled flexibility and comprehensive solutions, enabling them to invest

solely in what provides a clear business advantage and boosts profitability. VTEX is trusted by 2,400 global B2C and B2B

customers, including Carrefour, Colgate, Motorola, Sony, Stanley Black & Decker, and Whirlpool, having 3,400 active online stores

across 43 countries (as of FY ended on December 31, 2024).

Founded in the year 2000, VTEX has a history of being unstoppable. Completely against the odds, VTEX is leading a high-tech

industry and positioned above market giants. We are building an extraordinary future with more than 1,300 employees scattered

across 25 locations in 16 countries in Latin America, North America, Europe, and Asia. For more information, visit www.vtex.com.

At VTEX, you will work in a challenge-driven environment and collaborate with amazing peers. If you are powerful individually,

join us, and we will be unstoppable together.

BENEFITS

Annual profit-sharing program and equity eligibility;
Health, dental, and life insurance with national coverage provided by VTEX;
Annual budget for professional development in Tech;
Language development incentive program (English, Spanish, Portuguese);
Flexible meal allowance;
Extended parental leaves;
Child-care assistance;
Flexible work schedule and remote-first culture;
Financial assistance to build your work-from-home setup;
Wellness program;
Free shipping on 1000+ VTEX stores

#LI-REMOTE

Role

Data Engineer, Data Platform

Tags for this job

Python AWS Azure GCP Docker Kubernetes SQL NoSQL AI Machine Learning Rust Terraform Kafka Spark

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