Data Engineer - Real-Time MEM SQL & Pipelines

Qode; Floridablanca; Presencial; COP 366.740.000 - 533.440.000; Jornada completa

Descripción de la vacante

Qode is seeking an experienced Data Engineer to design and optimize scalable MEM SQL-based data pipelines and platforms. You will work closely with data scientists, analysts, and application teams to deliver high-performance solutions.

The role requires strong SQL skills, data modeling knowledge, and hands-on ETL experience, with exposure to cloud platforms and big data tools (Spark/Kafka). You will ensure data quality, security, and reliability across data ecosystems.

Formación

• Experienced Data Engineer with strong MEM SQL (SingleStore) expertise.
• Solid SQL skills and database optimization experience.
• Hands-on ETL tools and data pipeline frameworks.
• Knowledge of data modeling and data warehousing concepts.
• Experience handling large datasets and real-time data processing.
• Familiarity with cloud platforms and Big Data technologies (Spark, Kafka).

Responsabilidades

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Work extensively with MEM SQL (SingleStore) for real-time and large-scale data processing.
• Optimize database performance, queries, and data models.
• Collaborate with data scientists, analysts, and application teams to support data needs.
• Ensure data quality, reliability, and security across data platforms.
• Monitor and troubleshoot data pipeline and system issues.
• Support data migration and integration activities.

Conocimientos

Data Engineer

MEM SQL

SQL

ETL tools

Data modeling

Real-time data processing

Large datasets

Herramientas

MEM SQL (SingleStore)

Spark

Kafka

Cloud platforms (AWS/Azure/GCP)

Descripción del empleo

Qode is seeking an experienced Data Engineer to design and optimize scalable MEM SQL-based data pipelines and platforms. You will work closely with data scientists, analysts, and application teams to deliver high-performance solutions.

The role requires strong SQL skills, data modeling knowledge, and hands-on ETL experience, with exposure to cloud platforms and big data tools (Spark/Kafka). You will ensure data quality, security, and reliability across data ecosystems.