The Role

Behind Avra's Foundation AI sits a critical layer: a data platform that ingests, structures, and operationalizes messy, real-world data into reliable inputs for our models and products.

As a Senior Data Engineer, you’ll play a key role in building and running the heart of that data platform. This isn’t just about “moving data from A to B.” You’ll take ownership of systems that turn messy, unpredictable, external data into reliable datasets—powering our models, guiding decisions, and driving revenue.

You’ll have the chance to work across every part of our platform: from data ingestion pipelines and orchestration layers, to warehouse models and infrastructure. Along the way, you’ll make thoughtful engineering trade-offs and always be on the lookout for ways to make our systems better and more efficient.

This role is perfect for someone who knows that data engineering is truly an operational craft. You won’t just be building pipelines—you’ll be responsible for ensuring that the systems you create stand the test of time, staying reliable even as things change and scale. We’re looking for someone excited to take on that challenge!

📍 Remote (Brazil)

Responsibilities

• Pipeline & Workflow Orchestration. Design and operate orchestrated workflows, ensuring clear execution semantics, observability, and resilience.

• Data Modeling & Transformation. Design and maintain scalable transformation layers using dbt, BigQuery, Spark, Ray or equivalent tools, enabling reliable downstream consumption.

• Data Quality & Platform Standards. Define and enforce standards around data quality, contracts, schema validation, lineage, and metadata.

• Handling Real-World Data Complexity. Work with incomplete, inconsistent, and evolving data sources. Handle schema drift, edge cases, and operational failures with strong engineering judgment.

• Cloud & Infrastructure Integration. Operate within cloud-native environments (GCP/AWS), working with storage, messaging (e.g., Pub/Sub), and infrastructure as code.

• Platform Improvement & Simplification. Continuously improve systems by increasing observability, reducing operational risk, and simplifying architecture.

You Stand Out If

• You have strong experience operating production data systems, not just building them once

• You have worked with orchestration tools like Dagster, Airflow, or Prefect

• You have experience designing robust data models and transformation layers

• You have strong hands-on experience with Python for data engineering (pipelines, tooling, and production systems)

• You think in terms of systems, reliability, and long-term maintainability

• You simplify complexity instead of adding unnecessary abstraction

• Experience with GCP, dbt, BigQuery, or event-driven architectures is a strong plus

Qualifications

• Experience - At least 5 years of experience building and operating data systems in production environments

• Technical Proficiency - Strong Python and SQL skills, with experience in data pipelines, orchestration, and warehouse modeling

• Operational Mindset - Experience managing data quality, observability, failure modes, and long-running production workflows

• Collaboration - Strong communication skills and ability to work across engineering, product, and business teams

What We Offer

• Competitive Compensation - Attractive salary and equity participation

• Ownership & Impact - Direct influence on the foundation of Avra’s data platform and its evolution

• Technical Environment - Work on real-world data problems involving complex ingestion, reliability, and large-scale systems

• Lean, High-Quality Team - Work closely with experienced engineers and founders in a high-context environment

• Flexible Culture - Remote-first (Brazil), with flexible time off and a strong focus on autonomy

If you are motivated by building and operating real data systems — not just designing them — and want to work on hard problems involving messy data and production reliability, we would like to hear from you.