Remote Data Pipeline Engineer

Hire Feed

Colombia

Presencial

COP 277.675.000 - 401.086.000

Jornada completa

hace 40 horas
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Descripción de la vacante

Hire Feed is seeking a Data Engineer for a full-time, remote role to design, build, and maintain scalable data pipelines and infrastructure. You will collaborate with cross-functional teams to deliver data solutions that support business insights and decision-making.

Responsibilities include developing ETL/ELT workflows, maintaining data warehouses and lakes, and ensuring data quality and accessibility for analysts and data scientists.

Formación

  • Proficiency in SQL and experience with relational and NoSQL databases.
  • Experience with ETL/ELT tools such as Airflow, Spark, or similar frameworks.
  • Knowledge of data modeling and warehouse design principles.
  • Familiarity with cloud platforms like AWS, GCP, or Azure for data infrastructure.
  • Strong problem-solving skills with attention to scalability and performance.

Responsabilidades

  • Design, develop, and optimize data pipelines to extract, transform, and load large datasets.
  • Implement and maintain data warehouses and data lakes to support analytical and operational reporting.
  • Collaborate with data scientists and analysts to ensure data accessibility and integrity.
  • Monitor pipeline performance and troubleshoot issues to ensure reliability and efficiency.
  • Document data architecture, processes, and standards for team reference and compliance.

Conocimientos

SQL
Relational DBs
NoSQL DBs
Data modeling
Data warehouses
Cloud platforms
Analytical thinking
Problem-solving

Herramientas

Airflow
Spark
ETL/ELT tools

Descripción del empleo

Hire Feed is seeking a Data Engineer for a full-time, remote role to design, build, and maintain scalable data pipelines and infrastructure. You will collaborate with cross-functional teams to deliver data solutions that support business insights and decision-making.

Responsibilities include developing ETL/ELT workflows, maintaining data warehouses and lakes, and ensuring data quality and accessibility for analysts and data scientists.

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