Data Analytics Engineer

jobr.pro; São Paulo; Presencial; BRL 120 000 - 160 000; Tempo integral

Resumo da oferta

Ebury is seeking a Data Analytics Engineer in São Paulo to help build and maintain our Data Platform. You will work with our Analytics Engineering team to ensure reliable data delivery for analysts and data scientists.

You will design, implement and govern data pipelines using dbt, BigQuery and Looker, applying solid software engineering practices and CI/CD. This role blends hands-on engineering with governance and data quality focus.

Qualificações

• 2+ years of data/analytics engineering experience building and maintaining data pipelines.
• Proficiency in SQL.
• Mid-level Python experience.
• Experience with modern data stack tools (dbt, GCP, Looker).
• Attention to data quality and governance.
• Strong English; Spanish a plus.

Responsabilidades

• Gather requirements and define an action plan to execute them.
• End-to-end delivery of projects from definition to deployment.
• Hands-on data modeling with version control, testing, and CI/CD.
• Promote best practices and quality across the platform.
• Manage overall pipeline orchestration using Airflow (Cloud Composer).
• Design, develop, deploy and maintain ELT/ETL data pipelines from various sources.
• Contribute to query development, code reviews, and documentation.

Conhecimentos

SQL

Python

Data pipelines

ETL

Data governance

Ferramentas

dbt

BigQuery

Looker

Airflow

Cloud Composer

Descrição da oferta de emprego

Data Analytics Engineer

Location: São Paulo (4 days on-site, 1 day remote)

Ebury is a FinTech success story, positioned among the fastest-growing international companies in its sector. Headquartered in London, we have more than 1,000 staff covering over 50 nationalities working across more than 27 offices worldwide and serving more than 45,000 clients every day.

About our team:

Ebury’s strategic growth plan would not be possible without our Data team and we are seeking a Analytics Engineer to join our Analytics Engineering team.

Our data mission is to develop and maintain Ebury’s Data Platform and serve it to the whole company, where Data Scientists, Data Engineers, Analytics Engineers and Data Analysts work collaboratively to:

• Build ETLs and data pipelines to serve data in our platform.
• Provide clean, transformed data ready for analysis and used by our BI tool.
• Develop department and project-specific data models and serve these to teams across the company to drive decision-making.
• Automate end solutions so we can all spend time on high-value analysis rather than running data extracts.
• Collaborate with stakeholders to understand the requirements, advising on and influencing the solutions, and taking ownership of data implementation and delivery.

About our technology and Data stack:

• Google Cloud Platform as our main Cloud provider.
• Apache Airflow as orchestration tool.
• Cloud Build as CICD.
• dbt as data modelling and warehousing.
• Looker and Looker Studio as Business Intelligence/dashboarding.
• Github as code management tool.
• Jira as project management tool.
• Among others third party tools such as Hevodata, Synq…

About the role:

As an Analytics Engineer, you will be an integral part of our data team. You will work closely with the rest of the team to help model and maintain the Data Platform. This role also encompasses important responsibilities in quality assurance, data governance, and promoting best practices to ensure that data-related processes are efficient, secure, and adhere to industry standards.

As part of the team you will

• Gather requirements from the business and define an action plan to execute them.
• Work on projects end to end, from definition to delivery.
• Serve hands‑on delivery of data models using solid software engineering practices (eg. version control, testing, CI/CD).
• Collaborate with team members to reinforce best practices across the platform, encouraging a shared commitment to quality.
• Manage overall pipeline orchestration using Airflow (hosted in Cloud Composer).
• Design, develop, deploy and maintain ELT/ETL data pipelines from a variety of data sources (transactional databases, REST APIs, file-based endpoints).
• Contribute to and promote best practices for query development, version control, code review, documentation, and testing.

What we’re looking for

• 2+ years of data/analytics engineering experience building, maintaining & optimizing data pipelines & ETL processes on big data environments.
• Proficiency in SQL.
• Mid-level experience with Python.
• Experience with modern data stack tools (a plus!). We use dbt, Google Cloud Platform (BigQuery, DataStudio), Looker.
• Familiarity with dimensional modelling / data warehousing concepts.
• Experience with software engineering practices in data.
• Attention to detail and commitment to data quality.
• Advanced in English (Spanish, a plus).

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