Data Engineer

hace 4 semanas

Buenos Aires, Argentina Modak A tiempo completo

**About us**:
Modak is a US-based platform leveraging the power of fintech, gamification, and community to empower teens to reach their full potential.

We are founded with an audacious vision to enable teens and young adults to reach their full potential, regardless of their background. We pursue this mission by offering a gamified fintech and learning ecosystem - with teen cards, financial literacy, and other services. We build for scale and security using the best technologies and enrich the user experience with a thriving community that supports each other. Modak is trusted by over 25,000 teenagers (and growing by the day).

We are a global company, with teams across the US and LatAm and we do in person retreats every 2-3 months. If you are hungry to learn, humble to work with, and hustle like no one else, we would love to hear from you - especially if you are living in the US, Bogota, or Buenos Aires.

We are one of the most well-funded early stage startups, and we are grateful for the 3+ years of runway we have even in this market. Our investors include GGV Capital ($9.2Billion VC firm), Monashees, Maya Capital, Nazca VC, One VC, and 30+ leading angel investors and entrepreneurs across Silicon Valley and Latin America.

**About this role**:
As a Data Engineer at Modak, you will play a pivotal role in designing and building scalable data solutions that power our platform. You'll collaborate with cross-functional teams to create infrastructure that drives insights, innovation, and better financial literacy experiences for kids and parents alike.

**Responsibilities**:
Data Pipeline Development
- Design, build, and maintain scalable ETL pipelines to collect, process, and transform structured and unstructured data from multiple sources.
- Ensure pipelines are optimized for efficiency, reliability, and scalability.
- Database Management
- Develop and optimize database schemas and queries for data warehousing solutions.
- Manage and maintain relational and non-relational databases (e.g., AuroraDB, DynamoDB).

Infrastructure Building
- Collaborate on building a cloud-based data platform (AWS) to support analytics and machine learning workflows.
- Implement distributed systems and tools for real-time and batch data processing (e.g., AWS SQs, AWS EventBridge).

Collaboration
- Work closely with data analysts and product teams to understand data needs and deliver usable solutions.
- Proactively engage with cross-functional teams to suggest and implement improvements to internal services.

**Qualifications**:

- Programming Languages: Proficiency in Python and SQL with a strong understanding of complex queries and performance optimization.
- Data Pipelines: Experience with ETL/ELT tools and frameworks (e.g., Apache Airflow, Prefect, AWS Glue).
- Cloud Expertise: Hands-on experience with AWS or other cloud platforms (Google Cloud, Azure).
- Databases: Expertise in relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, DynamoDB).
- Version Control: Familiarity with Git.
- CI/CD: Experience implementing and managing CI/CD pipelines.

**Bonus Qualifications**:

- AWS certifications (e.g., AWS Certified Data Analytics or AWS Certified Solutions Architect).
- Proficiency in Go (Golang).
- Experience with Snowflake, Redshift, or BigQuery.

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