Data Engineer
Design and develop reusable workflows for data ingestion, transformation, and quality while building scalable ETL pipelines. Implement data governance policies and migrate legacy data warehouses to cloud environments.
19 Data Engineer jobs in Chile available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, Data Engineer Senior - Colombia and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and develop reusable workflows for data ingestion, transformation, and quality while building scalable ETL pipelines. Implement data governance policies and migrate legacy data warehouses to cloud environments.
The role involves designing, building, and optimizing data infrastructure on a corporate Data Lake while implementing scalable batch and streaming data pipelines. You will also manage data governance, security standards, and lead complex technical implementations within data and analytics projects.
Design, integrate, and maintain end-to-end data pipelines to support market projections and sales processes. Ensure data quality, governance, and efficient monitoring within a team guided by a Technical Lead.
You will build and operate scalable ingestion, ELT/ETL, and orchestration pipelines to transform raw data into clean, AI-ready datasets. Additionally, you will implement real-time data ingestion flows and ensure high data quality through rigorous testing and observability.
Design, develop, and maintain scalable data pipelines to support ingestion, transformation, and delivery for model-training and real-time inference. Oversee vector data stores and implement AI-backed analytics solutions to enable advanced search and retrieval patterns.
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The Senior Data Engineer will own the end-to-end data pipeline architecture, connecting paid media platforms and CRMs into a centralized BigQuery warehouse. They are responsible for building modular transformation pipelines, ensuring data quality, and enabling performant reporting for marketing teams.
Design, develop, and maintain scalable cloud-based data infrastructures and pipelines. Manage data ingestion processes into the datalake while ensuring data quality, integrity, and availability.
The Senior Data Engineer will design, build, and maintain scalable ELT pipelines using Snowflake, dbt, and Apache Airflow. They will also mentor team members, optimize platform performance, and support downstream reporting through modern BI tools.
The role involves transforming raw data into reliable assets by designing and optimizing data pipelines for omnichannel ingestion and activation. You will also be responsible for ensuring data governance, quality, and automating monitoring alerts within the marketing platform.
Design, develop, and maintain data engineering solutions using Python and Azure services while building scalable pipelines for data processing. Collaborate with multidisciplinary teams to develop business-oriented solutions and integrate internal and external systems via APIs.
The Data Engineer will design, develop, and maintain data pipelines while integrating information using various Google Cloud Platform services. They will also be responsible for implementing transformation and modeling processes using Dataform and orchestrating workflows with Apache Airflow.
Design, develop, and maintain data pipelines while optimizing ETL processes and integration flows. Collaborate with multidisciplinary teams to ensure data quality, integrity, and availability within scalable environments.
Design, develop, and implement scalable Generative AI solutions using Python and LLMs. Manage cloud infrastructure as code and integrate AI components into productive environments.
Design, build, and own scalable data pipelines and ingestion processes primarily on the Snowflake Data Cloud. Lead the architecture of data models and enforce governance and security standards across the platform.
Design and implement scalable data architectures on Azure while leading technical definitions and best practices. Collaborate with business teams to transform requirements into high-impact data solutions and mentor team members.
The role involves building production-grade agentic workflows and LLM-powered systems while managing data pipelines and semantic context layers. You will also be responsible for establishing evaluation practices, observability, and providing technical leadership to clients.
Design, develop, and manage enterprise data integration pipelines using Informatica IDMC to feed Databricks Lakehouse. Optimize ETL/ELT processes and ensure scalability, performance, and compliance with established SLAs.
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Design and implement a comprehensive data quality framework across Bronze, Silver, and Gold layers within Databricks pipelines. Collaborate with Data Engineering and business teams to validate data pipelines, perform reconciliation, and ensure production-ready data assets.
You will perform as a subject matter expert in Microsoft Purview and Collibra to develop data-driven solutions and intellectual property. Additionally, you will convert complex data into clear dashboards and monitor key performance indicators to support organizational decision-making.
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