ASAAS
ASAAS
501 – 1,000 Employees
ConsultingHealthcareHospitality
ASAAS develops immersive 360° virtual tours for businesses and organizations seeking more engaging digital experiences. Its work combines 360° video, drone capture, and interactive features to create customized virtual environments for sectors such as education, hospitality, museums, and healthcare. The company focuses on helping clients present their spaces and services online with richer, more interactive visual content.

Senior Analytics Engineering Tech Lead

Lead analytics engineering at Asaas, setting standards for data quality and automating its analytics platform. Advance dbt, CI/CD, governance, and observability for a fintech serving more than 200,000 customers.

Description

  • Set technical standards for Analytics Engineering at Asaas across data modeling, version control, testing, and documentation.
  • Architect a shared analytics platform layer designed for modularity, reuse, and scale.
  • Improve tools and developer workflows across dbt projects, macros, internal packages, CI/CD, environments, and templates.
  • Build and maintain data quality and observability practices, including automated tests, freshness checks, alerts, incident handling, and pipeline health metrics.
  • Partner with the Governance team to support reliable data through cataloging, documentation, access policies, and artifact lifecycle management.
  • Track data platform costs and performance, and optimize both.
  • Automate work and apply generative AI across the data lifecycle.
  • Follow developments in analytics engineering and turn relevant trends into team improvements.
  • Coach and grow team members through code reviews, pairing, and technical forums.
  • Build a collaborative, inclusive team focused on meaningful impact.

Requirements

  • Experience providing formal or informal technical leadership to data teams
  • Experience with dimensional modeling and the development of scalable analytics pipelines
  • Advanced SQL skills
  • Experience with dbt, including project organization, macros, tests, and documentation
  • Experience with Databricks, Unity Catalog, Asset Bundles, permission management, and environment management
  • Experience with Python for pipeline orchestration and automation, using Airflow or an equivalent tool
  • Experience with structured code version control using Git and GitHub
  • Experience applying software engineering practices to data, including CI/CD, code reviews, and automated testing
  • Experience defining and implementing scalable technical standards for other data teams
  • Degree or equivalent experience in Engineering, Data Science, Computer Science, Information Systems, Statistics, Economics, or a related field
  • Preferred: Previous experience in fintech, payments, or financial services
  • Preferred: Knowledge of infrastructure as code (IaC) using Terraform
  • Preferred: Experience productionizing machine learning projects applied to digital products
  • Preferred: Participation in digital product architecture projects, such as data mesh, event-driven architecture, and CDC
  • Preferred: Experience with statistical testing and measuring product impact

Benefits

  • Medical and dental insurance with no copay
  • Life insurance
  • Prescription medication assistance
  • Fitness allowance
  • Four free therapy or nutritionist sessions per month
  • Quick massage at headquarters
  • Flexible meal and food allowance on a Visa card
  • Complimentary food at headquarters
  • Childcare assistance
  • Parental support program
  • Extended maternity and paternity leave
  • In-house training platform
  • Education assistance covering 70% of tuition for undergraduate programs and language courses, as well as courses and books
  • Home office allowance
  • Work equipment
  • Furniture allowance
  • Partnership with WOBA for access to coworking spaces throughout Brazil
  • Birthday month day off
  • Happy hour allowance
  • Referral bonus for new hires
  • Bonus based on annual goals
  • Stock option plan
  • No dress code

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