Data Engineer Senior

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: Argentina (prefered Córdoba).

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, architects, 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, 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, Athena and step functions.
- Python.
- Snowflake.
- RDBMS (Oracle DB, MS SQL Server, MySQL, PostgreSQL).
- Apache Airflow, or other workflow management tools.
- SQL.
- Linux.

Nice to have:

- Spark.
- Docker.
- Testing.
- Pydantic.
- Azure data services, such as Data Factory.
- 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.
- Excellent communication skills, both verbal and written. Organizational skills and team building. Ability to share their knowledge and perspectives.
- Experience working with data lakes and data warehouses, preferentially Data Lake on AWS (or its underlying technologies), AWS Redshift, Snowflake, Azure Data Factory, etc.

Experience
- More than 5 years of concrete experience, working on real-life projects using- Structured datasets (e.g. CSV tables, Parquet / ORC files)
- Unstructured datasets (e.g. log files)
- RMDBs usage and management.
- Code versioning tools like Git
- More than 3 years of experience performing project tasks and bugs tracking on some platforms (e.g. JIRA, Trello)