Analytics Engineering – Tech Lead

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Act as the technical authority for Analytics Engineering at Asaas, establishing and upholding standards for modeling, version control, testing, and documentation.

• Lead the design of the shared analytics platform layer, ensuring it is modular, reusable, and scalable.

• Enhance tooling and the developer experience, including dbt projects, macros, internal packages, CI/CD, environments, and templates.

• Implement and sustain data quality and observability mechanisms, comprising automated tests, freshness monitoring, alerts, incident management, and pipeline health metrics.

• Collaborate with the Governance team to ensure data governance and reliability, covering cataloging, documentation, access policies, and artifact lifecycle management.

• Monitor and optimize both costs and performance of the data platform.

• Propel automation and incorporate Generative AI across the data lifecycle.

• Stay updated on analytics engineering trends and translate them into enhancements for the team.

• Mentor and advance the team through code reviews, pairing, and participation in technical forums.

• Cultivate a collaborative, inclusive, and impact-focused work environment.

⛳️ Requirements

• Proven experience in providing either formal or informal technical leadership to data teams.

• Familiarity with dimensional modeling and the creation of scalable analytics pipelines.

• Advanced proficiency in SQL.

• Experience with dbt, including project organization, macros, tests, and documentation.

• Knowledge of Databricks, Unity Catalog, Asset Bundles, permission management, and environment management.

• Proficient in Python for orchestrating and automating pipelines, utilizing Airflow or a similar tool.

• Skilled in structured code version control using Git and GitHub.

• Experience in applying software engineering practices to data, including CI/CD, code reviews, and automated testing.

• Ability to define and implement 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: Prior experience in fintech, payments, or financial services.

• Preferred: Understanding of infrastructure as code (IaC) using Terraform.

• Preferred: Experience in productionizing machine learning projects applied to digital products.

• Preferred: Involvement in digital product architecture projects, such as data mesh, event-driven architecture, and CDC.

• Preferred: Experience with statistical testing and evaluating product impact.

🏝️ Benefits

• Medical and dental insurance with no copay.

• Life insurance.

• Prescription medication assistance.

• Fitness allowance.

• Four free therapy or nutritionist sessions each month.

• Quick massage available at headquarters.

• Flexible meal and food allowance provided on a Visa card.

• Complimentary food offered at headquarters.

• Childcare assistance.

• Parental support program.

• Extended maternity and paternity leave.

• Access to an in-house training platform.

• Education assistance covering 70% of tuition for undergraduate programs and language courses, as well as other courses and books.

• Home office allowance.

• Provision of work equipment.

• Furniture allowance.

• Partnership with WOBA for access to coworking spaces across Brazil.

• Day off during the birthday month.

• Happy hour allowance.

• Referral bonus for new hires.

• Bonus based on annual goals.

• Stock option plan.

• No dress code.