Analytics Engineering – Tech Lead

ASAAS

. Serve as the technical authority for Analytics Engineering at Asaas, defining and ensuring standards for modeling, version control, testing, and documentation .

Posted 10/10/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Analytics Engineering, focusing on data modeling, version control, and testing while ensuring data quality and governance. Proficient in leading technical initiatives and mentoring teams to enhance the analytics platform and developer experience.

Highest-signal resume keywords

Advanced SQL SkillsExperience with dbtPython for Pipeline OrchestrationDimensional ModelingTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Dimensional ModelingAdvanced SQLPythonCI/CDAutomated TestingData GovernanceVersion ControlAnalytics Pipeline DevelopmentStatistical TestingMachine Learning Productionization

Soft Skills

MentoringCollaborationImpact Orientation

Tools & Technologies

DbtDatabricksAirflowGitGitHubTerraformUnity Catalog

Industry Keywords

FintechPaymentsFinancial ServicesData MeshEvent-Driven Architecture

Tech Stack

Tools & technologies

AirflowPythonSQLTerraformUnity

About the role

Key responsibilities & impact

Serve as the technical authority for Analytics Engineering at Asaas, defining and ensuring standards for modeling, version control, testing, and documentation
Lead the architecture of the shared analytics platform layer, ensuring modularity, reusability, and scalability
Advance tooling and the developer experience, including dbt projects, macros, internal packages, CI/CD, environments, and templates
Establish and maintain data quality and observability mechanisms, including automated tests, freshness monitoring, alerts, incident management, and pipeline health metrics
Ensure data governance and reliability in partnership with the Governance team, covering cataloging, documentation, access policies, and artifact lifecycle management
Monitor and optimize data platform costs and performance
Drive automation and apply Generative AI throughout the data lifecycle
Track analytics engineering trends and translate them into improvements for the team
Mentor and develop the team through code reviews, pairing, and technical forums
Foster a collaborative, inclusive, and impact-oriented environment

Requirements

What you’ll need

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

Comp & perks

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