Mid Data Engineer

Posted 3 Days Ago
Be an Early Applicant
Mexico, Cuauhtémoc, Mexico City, MEX
Hybrid
Junior
Fintech • Payments • Software • Financial Services
The Role
Build and maintain web scraping and browser automation systems, develop production Python services, design streaming and batch data pipelines, improve data reliability and observability, automate Revenue Ops workflows, debug failures, and improve engineering quality through tests, docs, logging, metrics, traces, and AI-assisted tooling.
Summary Generated by Built In

About Klar

We're turning one of the world's largest underbanked markets into something fairer, simpler, and more transparent. 7 million users served since 2019. Uber's first global credit card, built right here in Mexico. Klar Empresarial, a brand-new B2B solution — Klar Empresarial — bringing agile credit and smart accounts to SMEs who've been ignored by traditional banks for too long.

And a full banking license on the horizon, because our customers asked for it and we listened.

We move fast, we think big, and we go all in, because as our CEO puts it: "Growing doesn't always mean going further. Sometimes it means going deeper." 

Behind all of it is a team of 30+ nationalities, working across Mexico City, Berlin, and Argentina, obsessed with building financial products that are simpler, faster, and fairer than anything that came before.

This is Klar, and we're seeking the people who'll write the next chapter.

Our people

If you join us at Klar, you’ll be welcomed to a team that is rich in many talents and we are very proud! With our head office in Mexico City, and remote tech hubs in Berlin and Argentina, we are always learning something new about another culture or language. With so many people from different backgrounds and walks of life (young professionals, parents, LGBTQ+, neurodivergence), you’ll definitely find your people here! 

Our values

  • Ownership - We own our successes & our failures as a team.
  • Excellence - We do everything to the best of our ability & always seek to achieve a new level of excellence in our work.
  • Inclusion - We believe we are stronger together and actively work to promote a safe, diverse, inclusive, and respectful culture.
  • Customer Obsession - We understand the value Klar can bring to its customers & it’s always at the forefront of our decisions.
  • Klarity - We communicate clearly & with authenticity. It’s in our name & it’s what we do.

The position and your daily adventures

We’re currently looking for a Data Engineer to join our Revenue Ops team. As a Data Engineer your main responsibilities will be to build and maintain web scraping, extract data, create data pipelines and infrastructure. You will be in charge of creating real-time processes and alerts, improving data reliability and quality, and automating Revenue Ops workflows.

What you can expect:

  • Work remotely as part of the Revenue Ops team, collaborating asynchronously with product, operations, and engineering stakeholders.
  • Develop and maintain scraping services end to end, from credential handling and extraction flows to parser reliability and operational tooling.
  • Build and maintain production Python services across APIs, event-driven worker processes, relational persistence, and cloud-backed artifacts.
  • Design streaming and batch data flows that make business data reliable, timely, observable, and usable for Revenue Ops workflows.
  • Debug real-world scraping and data-processing failures involving external systems, browser automation, retries, providers, and artifact-based diagnostics.
  • Improve engineering quality through tests, clear documentation, structured logging, metrics, traces, and strategic use of modern AI-powered tools.

What we are looking for:

Mandatory

  • 2+ years of professional software engineering or data engineering experience building production Python services, with ownership of design, implementation, testing, and operations.
  • Strong Python backend experience with FastAPI or similar web frameworks, Pydantic-style validation, async workflows, and typed service boundaries.
  • Required knowledge of streaming data systems and event-driven processing, especially Kafka consumers/producers, partitioning, ordering, delivery semantics, retry/idempotency, backoff, and operational failure handling.
  • Solid database experience with PostgreSQL and SQLAlchemy/Alembic, including schema design, migrations, transactional boundaries, and performance-aware queries.
  • Practical experience building or maintaining web scraping/browser automation systems with Scrapy, Playwright, HTTP sessions, anti-bot constraints, and deterministic parser tests.
  • Experience handling sensitive credentials or confidential business data, including encryption, secret versioning, redaction, auditability, and least-privilege access patterns.
  • Comfort owning cloud-native services on AWS, including S3, KMS, containerized deployments, metrics, traces, and production incident debugging.
  • Advanced English and clear technical communication; able to read existing architecture, reason from tests and logs, document tradeoffs, and collaborate with product/ops stakeholders.
  • Comfort using modern AI-powered tools strategically to accelerate development, debugging, documentation, and analysis while applying sound engineering judgment.

Desirable

  • Experience with SAT, tax, fintech, invoicing, or other Mexican financial workflows.
  • Experience with worker/master architectures, Kubernetes, Docker Compose, horizontal scaling, worker concurrency, and queue-based scheduling.
  • Familiarity with proxy providers, browser fingerprint hardening, captcha/error classification, and safe live diagnostics for scraping systems.
  • Strong testing discipline with pytest, integration tests, replay/VCR-style fixtures, static analysis, and CI quality gates such as ruff and pyright.
  • Experience designing observable systems with structured logging, Prometheus metrics, OpenTelemetry traces, bounded labels, and explicit failure taxonomies.
  • Bonus: experience with Terraform, DBT, Redshift, Spark, Flink/RisingWave, or data orchestration tools, when relevant to adjacent data platform work.

Our offer to you:

  • Competitive salary based on performance and experience
  • Chance of earning Klar stock options
  • 15 days of paid vacation per year; plus extended maternity and paternity leaves
  • Vacation premium
  • 30 days of Christmas bonus
  • Food vouchers
  • Medical Insurance
  • Computer device
  • Wellhub  subscription to offer mental and physical health
  • Sponsored coaching and therapy sessions via a Mental Health platform  
  • A modern centrally located office in Mexico City with free drinks, snacks, and regular social events
  • International work environment with amazing and highly skilled people
  • A world class team that helps you evolve your skills in areas you're interested in

Klar is a safe place for everyone!

We trust our highly skilled and diverse team and we’re committed to creating a welcoming and inclusive environment for new talents to flourish. We value diversity and welcome all applications regardless of gender, nationality, ethnic and social origin, religion/belief, physical abilities, age, sexual orientation and identity.

Should you require any accommodations through the recruitment process, please don’t hesitate to let us know how we can help! 

Skills Required

  • 2+ years of professional software engineering or data engineering experience building production Python services, owning design, implementation, testing, and operations
  • Strong Python backend experience with FastAPI or similar web frameworks, Pydantic-style validation, async workflows, and typed service boundaries
  • Required knowledge of streaming data systems and event-driven processing, especially Kafka consumers/producers, partitioning, ordering, delivery semantics, retry/idempotency, backoff, and failure handling
  • Solid database experience with PostgreSQL and SQLAlchemy/Alembic, including schema design, migrations, transactions, and performance-aware queries
  • Practical experience building or maintaining web scraping/browser automation systems with Scrapy, Playwright, HTTP sessions, anti-bot constraints, and deterministic parser tests
  • Experience handling sensitive credentials or confidential data, including encryption, secret versioning, redaction, auditability, and least-privilege access patterns
  • Comfort owning cloud-native services on AWS, including S3, KMS, containerized deployments, metrics, traces, and production incident debugging
  • Advanced English and clear technical communication; able to read architecture, reason from tests/logs, document tradeoffs, and collaborate with stakeholders
  • Comfort using modern AI-powered tools strategically to accelerate development, debugging, documentation, and analysis while applying sound engineering judgment
  • Experience with worker/master architectures, Kubernetes, Docker Compose, horizontal scaling, worker concurrency, and queue-based scheduling
  • Familiarity with proxy providers, browser fingerprint hardening, captcha/error classification, and safe live diagnostics for scraping systems
  • Strong testing discipline with pytest, integration tests, replay/VCR-style fixtures, static analysis, and CI quality gates such as ruff and pyright
  • Experience designing observable systems with structured logging, Prometheus metrics, OpenTelemetry traces, bounded labels, and explicit failure taxonomies
  • Bonus: experience with Terraform, dbt, Redshift, Spark, Flink/RisingWave, or data orchestration tools
  • Desirable: experience with Mexican financial workflows (SAT, tax, fintech, invoicing) for domain knowledge
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The Company
351 Employees

What We Do

Klar is a Mexican digital bank and financial services platform that provides a secure, transparent, and free alternative to traditional banking services. Utilizing an app-based platform, the company offers a variety of deposit and credit services, including credit cards and loans. By leveraging AI-powered underwriting, Klar specifically targets Mexico's underbanked population to enable rapid customer acquisition and efficient credit decisioning.

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