Data Engineer

**About Fligoo**

Fligoo is an emerging leader in the Enterprise AI category, having built a technology architecture and suite of products that enable rapid development, deployment, and scaling across large enterprises.

At the moment, we are developing the next generation of AI technology for the Wealth Management and Financial Services industries. Fligoo’s technology leverages AI to allow the most important firms in the world to increase wallet share, predict client attrition, retain financial advisors, increase ROE, among others, significantly growing and protecting AUM. Companies we partner with include Wells Fargo, Cetera, Broadridge, PNC, JPMorgan, among others.

With the acquisition of Mobi To Buy and with offices around the globe in San Francisco, New York, São Paulo, Rio de Janeiro and Córdoba, Fligoo is currently one of the biggest Artificial Intelligence companies in the world.

Our long term vision is to become the most recognized technology company through our work helping our clients improve people’s lives offering solutions to complex problems by leveraging the most valuable asset of our time: data.

**About Position**Overview

**Location**: Córdoba (not fully remote).

**Position**: Full-Time

**Job Purpose**

The **Data Engineer** is responsible for building and maintaining the data architecture of a solution, as well as optimizing data flow and collection for cross-functional teams. The ideal player is an experienced data pipeline builder with strong skills in software engineering who enjoys developing and optimizing data systems.

The Data Engineer will support our software developers, data architects, data analysts and data scientists on their initiatives and will ensure optimal delivery is consistent throughout ongoing projects.

**Responsibilities**:

- Implement and maintain the data architecture required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Develop processes to handle large, complex data sets that meet functional / non-functional business requirements.
- Assess the effectiveness of data by conducting data quality checks.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, security aspects addressing, re-designing infrastructure for greater scalability, etc.
- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.

**Qualifications**:

- Academic training
- Degree in Computer Science, Statistics, Mathematics or other quantitative fields.
- A Master's or Ph.D. in those fields is a plus.
- Technical Skills
- AWS platform with experience in Glue, Lambdas, and Step Functions.
- RDBMS (Oracle DB, MS SQL Server, MySQL).
- Apache Airflow, or other workflow management tools.
- Linux.
- Python.
- Testing (pytest).
- Other Skills
- Advanced English level. Able to participate in an extended discussion on a variety of technical topics with only occasional disruptions, hesitations, or pauses.
- Nice to have: some knowledge on Spark and virtualization (Docker).
- Excellent communication skills, both verbal and written. Organizational skills and team building. Ability to share their knowledge and perspectives.

Experience
- 1+ years working with real-life projects, using datasets of the following kind:

- Structured data (e.g. CSV tables, Parquet / ORC files).
- Unstructured data (e.g. log files).
- 1+ years working with real-life projects:

- RMDBs usage and management.
- 1+ years performing project tasks and bugs tracking on some platform (e.g. JIRA, Trello)
- 2+ years of code versioning through a system like Git or Bitbucket.