Data Engineer: Build Scalable Pipelines & Trusted Data

StartX; Bogotá; On-site; COP 90,000,000 - 130,000,000; Full time

Benefits offered by this job

Health benefits

Life Insurance

Indefinite-term contract

20 vacation days

Co-working travel perk

Professional development perk

Home office equipment allowance

Catered lunches

Job summary

PayJoy is seeking a Data Analyst to design, build, and maintain robust data infrastructure and pipelines that feed analytics, reporting, and data-driven products. You will transform raw data into clean, well-governed datasets in the data warehouse/lake, enabling timely insights for business decisions.

You will work with analysts, data scientists, and stakeholders, ensuring data quality, security, and cost efficiency while using tools like Airflow, dbt, and cloud data warehouses.

Qualifications

• Proficiency in SQL and Python for data engineering.
• Experience with ETL/ELT, orchestration tools (Airflow, dbt).
• Experience with cloud data warehouses (BigQuery, Snowflake, or Redshift).
• Proficiency with at least one major cloud (GCP/AWS/Azure).
• Version control with Git.

Responsibilities

• Design, build, and maintain scalable data pipelines from multiple sources into data warehouse/lake.
• Develop and maintain data models, schemas, and transformations for analytics-ready datasets.
• Ensure data quality, governance, validation, testing, monitoring, and documentation.
• Optimize storage, query performance, and pipeline cost; troubleshoot failures with robust error handling.
• Collaborate with analysts, scientists, and business teams to deliver datasets and infrastructure.
• Apply security and compliance best practices for data handling and access controls.

Skills

SQL

Python

Airflow

dbt

BigQuery

Snowflake

Redshift

Cloud platforms

Git

Tools

Airflow

dbt

BigQuery

Snowflake

Redshift

Git

Job description

PayJoy is seeking a Data Analyst to design, build, and maintain robust data infrastructure and pipelines that feed analytics, reporting, and data-driven products. You will transform raw data into clean, well-governed datasets in the data warehouse/lake, enabling timely insights for business decisions.

You will work with analysts, data scientists, and stakeholders, ensuring data quality, security, and cost efficiency while using tools like Airflow, dbt, and cloud data warehouses.