Data Engineer: Build Scalable Pipelines & Trusted Data

PayJoy, Inc; Bogotá; Híbrido; COP 90.000.000 - 130.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Life Insurance

Indefinite-term contract

20 days vacations

Unlimited sick leave

Co-working Travel perk

Professional Development perk

Phone finance

Headphone benefit

Home office equipment allowance

Wellness perks

Catered lunches

Descripción de la vacante

PayJoy, Inc is seeking a Data Analyst to design and maintain data infrastructure, pipelines, and models that deliver clean, reliable data across the organization. You will transform raw data into structured datasets in the warehouse/lake, enabling analytics, reporting, and data-driven products.

The role focuses on accuracy, timeliness, scalability, and governance to support analysts, data scientists, and business teams making informed decisions.

Formación

• Proficient in SQL and Python for data engineering tasks.
• Experience with ETL/ELT and orchestration tools (Airflow, dbt).
• Knowledge of cloud data warehouses (BigQuery, Snowflake, Redshift).
• Version control experience (Git) and data modeling fundamentals.

Responsabilidades

• Design, build, and maintain scalable data pipelines (ETL/ELT) into data warehouses/lakes.
• Develop data models, schemas, and transformations for analytics-ready datasets.
• Ensure data quality, governance, validation, monitoring, and documentation.

Conocimientos

SQL

Python

ETL/ELT

Airflow

dbt

BigQuery

Snowflake

Redshift

Git

Herramientas

Airflow

dbt

BigQuery

Snowflake

Redshift

Git

Descripción del empleo

PayJoy, Inc is seeking a Data Analyst to design and maintain data infrastructure, pipelines, and models that deliver clean, reliable data across the organization. You will transform raw data into structured datasets in the warehouse/lake, enabling analytics, reporting, and data-driven products.

The role focuses on accuracy, timeliness, scalability, and governance to support analysts, data scientists, and business teams making informed decisions.