Staff Data Engineer

• 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)

• 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

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.