Data Analytics Engineer at Ebury

São Paulo, São Paulo, Brazil -

Full Time

Start Date

Immediate

Expiry Date

05 Jul, 26

Salary

0.0

Posted On

06 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Pipelines, ETL, ELT, Google Cloud Platform, Apache Airflow, dbt, Looker, Data Modeling, Data Warehousing, CI/CD, Version Control, BigQuery, Data Quality, Software Engineering

Industry

Financial Services

Description

Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. 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 (and counting!) 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 & optimising data pipelines & ETL processes on big data environments Proficiency in SQL Mid - Level experience with Python Experience with our 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) #LI-JC1 #LI-HYBRID About us Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally. Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 1,800+ Eburians across nearly 70 cities and we’re always looking to add to our team. At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage. The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars. We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.

Responsibilities

The Analytics Engineer will build and maintain ETL/ELT data pipelines and develop department-specific data models to drive company decision-making. They will also collaborate with stakeholders to define requirements and ensure data quality through best practices in orchestration and software engineering.