Semi Senior Data Engineer

Worldwide | Sept. 2, 2026

Report as Closed

Company: BC Tecnología

Country: Worldwide

Type: Remote

Employment: Full-time

Description: We are an IT consulting firm with expert staff in different areas of technology.

At BC Tecnología we manage portfolios, develop projects and offer outsourcing services and selection of professionals for clients in sectors such as financial services, insurance, retail and government. You will participate in strategic digital transformation initiatives for LATAM Airlines, a leading organization in the aeronautical industry, in an environment that combines remote work with occasional office presence. You will be part of the Architecture Management, collaborating in the definition of the business architecture and its evolution in the face of technological and business changes, ensuring alignment with the corporate strategy and governance standards.

Exclusive requirements

  • From 3 years of experience as a Data Engineer, Data Engineer or similar positions.
  • Practical experience with Databricks.
  • Mastery of advanced SQL (optimization, performance analysis and query quality).
  • Experience developing processes ETL/ELT for relevant volumes.
  • Experience working with large volumes of data.
  • Knowledge of data modeling (structures for analytical/operational consumption).
We want you to identify with
  • Orientation to quality and traceability: validations, monitoring and control of
  • Scalability mentality: think about performance, costs and maintainability.
  • Collaboration and clear communication with technical and business teams.
  • Operational responsibility: act on incidents and propose preventive improvements.
Desirable requirements (not exclusive) to accelerate your impact from the start.
  • Experience with AWS (S3, Glue, Lambda or Redshift).
  • Python.
  • Apache Spark / PySpark.
  • Delta Lake.
  • Airflow or other orchestration tool.
  • Knowledge of Data Lake and Data Warehouse.
  • Experience with CI/CD for data projects.
At BC Tecnología we value constant learning, inclusion and respect; That is why we promote a collaborative way of working, where the exchange of knowledge between teams strengthens the results of the project.
At BC Tecnología we are an IT consultancy that builds and evolves tailored solutions for clients in financial services, insurance, retail and government. We work with a clear focus on the client and agile methodologies, forming teams for Technological Infrastructure, Software Development and Business Units. In this project, we will join a team focused on the development and evolution of data platforms in the cloud. The mission of the area is to enable a robust and scalable platform for ingestion, transformation, processing and analytical/operational consumption, guaranteeing quality, availability and traceability of information. You will participate in the design of scalable data architectures, process automation and coordination with Analytics, BI, Data Science and business to ensure that data is transformed into value.
Main responsibilities
In the role of Data Engineer, our objective is to design, build and optimize reliable and scalable data pipelines, ensuring that the platform works stably in the cloud and delivers usable information for analytics and operation.
  • Design, develop and maintain data ingestion, transformation and processing pipelines.
  • Build and optimize processes ETL/ELT for large volumes of information.
  • Develop integration solutions using Databricks.
  • Model and structure data for analytical and operational consumption.
  • Optimize SQL queries and data processing processes to improve performance and costs.
  • Ensure quality, availability and information traceability (validations, monitoring and controls).
  • Participate in the definition and improvement of scalable data architectures.
  • Collaborate with Analytics, BI, Data Science and business teams to align requirements and ensure correct use of data.
  • Monitor and resolve incidents related to data platforms, applying good operational and observability practices.

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