Clara is the leading platform in Latin America for companies to execute and manage every payment operation. More than 50,000 leading and fast-growing businesses run on our corporate cards, bill pay, financing and B2B payments, and in 2025 the Financial Times named Clara the region’s fastest-growing company. We’re passionate about helping every company we work with become more effective—and, through that, raising the region’s competitiveness. We’re ~400 people, backed by Notable Capital, Coatue, Kaszek, monashees, DST Global, ICONIQ, General Catalyst and Goldman Sachs, among others.
We are looking for a Staff Data Engineer to be the technical backbone of our Data organization. You will be part of the team owning the architecture of our data platform and making sure our data is ready for the AI era. This is a hands-on, individual-contributor role: you will spend most of your time designing and building, not managing people.
You will:
- Own the technical vision and architecture of Clara's data platform, from ingestion and storage to modeling, serving and consumption
- Design and build scalable, reliable, cost-efficient data pipelines (batch and streaming) that support analytics, machine learning and operational use cases
- Lead our AI enablement efforts: structure, document and expose data (semantic layers, curated datasets, metadata, feature stores, retrieval-ready data) so that people, models and AI agents across the company can use it safely and effectively
- Define and drive best practices in data modeling, testing, observability, CI/CD, lineage and data quality
- Partner with the Director of Data to translate business and strategic goals into technical roadmaps, and to evaluate build-vs-buy decisions
- Implement the technical foundations of our data governance strategy: access control, PII handling, auditability and compliance, which matter in a regulated fintech environment
- Advance our self-service data platform so analysts, data scientists and business teams can work autonomously
- Collaborate closely with Engineering, Product, Risk, Growth, Marketing and Operations to ensure data is captured correctly at the source
- Raise the technical bar of the team through code reviews, design reviews, mentoring and technical documentation, without formal people-management responsibilities
- Stretch and adapt to a dynamic and fast-paced work environment
- 10+ years of experience in data engineering or software engineering with a data focus, including significant experience building and scaling data platforms at a top-tier tech company (fintech/startup experience is a plus)
- Proven track record designing and operating production-grade data architectures (lakehouse/warehouse, ELT/ETL, orchestration, streaming) at scale
- Deep proficiency in SQL and Python; experience with distributed processing frameworks (e.g. Spark) and orchestration tools (e.g. Airflow, Dagster)
- Experience building tooling for AI agents or LLM applications on top of enterprise data (text-to-SQL, MCP, RAG pipelines)
- Hands-on experience preparing data for ML and AI use cases (feature engineering, vector stores/embeddings, semantic layers, LLM-ready data) or a clear track record of moving quickly into this space
- Strong experience with cloud data platforms and infrastructure (AWS, GCP or Azure), plus infrastructure-as-code and CI/CD practices
- Strong command of data modeling, data quality, observability and governance best practices
- Experience with modern data stack tools (e.g. dbt, Databricks, Snowflake, BigQuery, Kafka)
- Ability to make sound architectural trade-offs (scalability, cost, reliability, speed of delivery) and communicate them clearly to technical and non-technical audiences
- Strong interpersonal and communication skills; comfortable influencing without authority and working closely with a Director-level leader
- Bachelor's degree in Computer Science, Engineering, Math, or another relevant quantitative discipline (or equivalent practical experience)
Nice to have:
- Experience in payments, credit, cards or other regulated financial services
- Experience with data catalogs, metadata management and data contracts
- Open-source contributions or technical writing/speaking
Where we work
This is a hybrid role: you'll split your time between the office, customers and home. We don't set a minimum number of office days for most roles — you'll spend time in the office naturally, and most days during your ramp-up or when your leader asks.
- A high talent-density team driven to make an impact in Latin America — low ego, high ownership.
- Competitive salary and stock options (ESOP) from day one.
- An annual learning budget and accelerated development paths.
- English is our working language, with Spanish and Portuguese every day.
- Clarity — Open and direct communication: we say what we mean and give context where it matters.
- Simplicity — If it can be simpler, it should be.
- Ownership — We own everything we do, end to end. When something needs to happen, we don't wait.
- Pride — We hold ourselves to a high standard, and it shows in what we deliver.
- ABC (Always Be Changing) — We adapt fast, embrace change, and keep learning.
- Inclusivity — Diverse ideas, stories and perspectives build a better Clara.
If you meet the must-haves, apply — the nice-to-haves are a bonus, not a requirement.
Skills Required
- 10+ years of experience in data engineering or software engineering with a data focus
- Significant experience building and scaling data platforms at a top-tier technology company
- Experience designing and operating production-grade data architectures, including lakehouse or warehouse, ELT/ETL, orchestration, and streaming
- Deep proficiency in SQL and Python
- Experience with distributed processing frameworks such as Spark
- Experience with orchestration tools such as Airflow or Dagster
- Experience building tooling for AI agents or LLM applications, including text-to-SQL, MCP, or RAG pipelines
- Hands-on experience preparing data for machine learning and AI use cases, including feature engineering, vector stores, embeddings, semantic layers, or LLM-ready data
- Strong experience with AWS, GCP, or Azure
- Experience with infrastructure-as-code and CI/CD practices
- Strong command of data modeling, data quality, observability, and governance
- Experience with modern data stack tools such as dbt, Databricks, Snowflake, BigQuery, or Kafka
- Ability to make and communicate architectural trade-offs involving scalability, cost, reliability, and delivery speed
- Strong interpersonal and communication skills, including influencing without authority
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or another relevant quantitative discipline, or equivalent practical experience
- Experience in payments, credit, cards, or regulated financial services
- Experience with data catalogs, metadata management, and data contracts
- Open-source contributions or technical writing or speaking
Clara Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Clara and has not been reviewed or approved by Clara.
-
Equity Value & Accessibility — Equity grants are emphasized across several descriptions, with stock options commonly included and in some instances available from day one. Feedback suggests this ownership component is a meaningful part of total rewards.
-
Leave & Time Off Breadth — Time off offerings are portrayed as flexible, including references to flexible vacation and flexible time off policies. Feedback suggests this supports work–life balance for many roles.
-
Wellbeing & Lifestyle Benefits — Wellness support is cited through mental‑health platforms, coaching and meditation programs, and monthly wellness reimbursements in some contexts. Feedback suggests these offerings complement core benefits where available.
Clara Insights
What We Do
Clara is the leading payment platform for companies in Latin America. Our end-to-end solution includes our locally-issued corporate cards, Bill Pay, crossborder payments, and our highly-rated software platform used by thousands of the most successful companies across the region. Clara is backed by top global and regional investors such as Coatue, DST Global, General Catalyst, monashees, Kaszek, Canary, A*, BoxGroup, SV Angel, GFC, Picus Capital, Avid Ventures, ICONIQ Growth, Goldman Sachs, and prominent angel investors. Driven by our six core values (Ownership, Pride, ABC, Simplicity, Clarity and Inclusivity) we’ve reached a unicorn valuation in record time, have been recognized as a Great Place to Work and as one of the most promising startups according to Linkedin’s ranking “Top Startups 2021”. We’re looking for the best talent worldwide to join our team and be part of this journey, so you can't afford to miss this chance! We are: * Shaping business finances in Latin America * Driven by our 6 core values * Proud of our inclusive and caring culture * Certified as a Great Place to Work and a Top LinkedIn Startup
.png){kind=logo}
