68 Data Engineer jobs in Colombia available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Data Engineer designs, develops, and maintains reliable data pipelines, transformations, and models to support analytics and operational workflows. They collaborate with cross-functional teams to translate business requirements into secure, scalable, and high-quality data solutions.
You will build and maintain reliable data pipelines and ETL/ELT workflows while developing optimized data models for analytics. Additionally, you will support core data platform tools and contribute to the architecture and roadmap of the data lakehouse.
The role involves executing and monitoring ETL/ELT processes and data pipelines while supporting the migration and decommissioning of DataMarts. The engineer will perform troubleshooting, data reconciliation, and maintain technical documentation to ensure data quality and process continuity.
You will design and implement scalable, domain-oriented data solutions and reliable pipelines on AWS. You will also collaborate with cross-functional teams to align technical solutions with business requirements and optimize data workflows.
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Design, build, and maintain scalable data pipelines and ETL/ELT processes using Databricks and Apache Spark. Implement CDC solutions and collaborate with cross-functional teams to support analytics and AI/ML use cases.
The Data Engineer - Snowflake Administrator is responsible for the secure, reliable, and well-governed administration of the Snowflake platform. This includes managing access, implementing security configurations, automating administrative tasks, and supporting data governance processes.
Define and implement architectural solutions to ensure the scalability and speed of data pipelines using Medallion Architecture. Lead the adoption of cloud-native solutions and drive best practices for ETL/ELT workflows, data governance, and security.
The role involves managing data collection and ingestion pipelines to support large-scale AI model training. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for consumer and enterprise products.
The role involves managing data collection operations to support model training and maintaining cloud infrastructure for ingestion pipelines. You will collaborate with scientists to optimize data quality and scale while contributing to the AI team's dataset roadmap.
Design and deliver end-to-end healthcare data architectures using Snowflake, dbt, and Azure tools. Lead technical delivery across the full software development lifecycle while facilitating requirements alignment with clinical and business stakeholders.
Design and maintain scalable data pipelines to ingest and normalize AI usage and billing data from multiple providers into a unified BigQuery model. Collaborate with cross-functional teams to build Power BI dashboards that provide actionable insights into AI spend, cost allocation, and forecasting.
Design, develop, and maintain data pipelines to migrate financial data from legacy Oracle databases to an Oracle ERP environment. Collaborate with stakeholders to translate business rules into data mappings while utilizing AI tools to streamline integration and validation processes.
Design and develop scalable data architectures and cloud-based data solutions using GCP services. Collaborate with stakeholders to build reliable data pipelines and integrate AI-driven workflows.
You will design and operate batch and streaming data pipelines on Databricks using a medallion architecture. Additionally, you will migrate legacy ETL workloads to the Lakehouse while ensuring data quality and governance.
Design, build, and operate batch and streaming data pipelines on Databricks using PySpark and Delta Lake. Migrate legacy ETL workloads to a governed Lakehouse architecture while ensuring data quality and performance optimization.
Design, build, and maintain scalable DBT models on Azure Databricks while leveraging AI-assisted tools for development and testing. Collaborate with engineering teams to implement data quality frameworks and ensure data products align with business objectives.
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The Staff Data Engineer will define data architecture and platform strategy while leading the design of scalable data lakes, warehouses, and pipelines. They will also mentor junior engineers and collaborate with cross-functional teams to integrate AI-forward solutions into enterprise operations.
The Senior Data Engineer will own the ingestion, pipeline orchestration, and Single Source of Truth architecture for new product modules. They will build containerized data pipelines on AWS and manage the data lifecycle from extraction through user acceptance testing.
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.
Design, build, and maintain the core data foundation including ingestion, modeling, and data marts to support agency, client, and AI initiatives. Collaborate cross-functionally to translate requirements into data solutions while optimizing pipelines for performance and cost.
You will serve as the primary guardian of the data ecosystem, championing data quality and ensuring the integrity of generated data. Additionally, you will own the data footprint that supports scalable production environments and bridge the gap between technical infrastructure and business logic.
Design, build, and maintain DBT models on Azure Databricks using Medallion Architecture and Unity Catalog. Implement AI-assisted development strategies to enhance code quality, productivity, and data governance standards.
The Senior Data Engineer will design, develop, and maintain complex data ingestion pipelines and Databricks Lakehouse architectures. They will also perform database performance tuning, query optimization, and collaborate with engineering teams on data access and migration initiatives.
The role involves owning the end-to-end delivery of data pipelines and products from design through deployment and production support. You will also be responsible for executing large-scale data migrations and managing infrastructure-as-code solutions.
You will architect and build an enterprise data platform from the ground up using Snowflake and Azure, managing the full stack from infrastructure to data modeling. Additionally, you will implement CI/CD pipelines, enforce data governance standards, and ensure platform observability and health.
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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 maintain scalable ELT/ETL pipelines and datasets to support cloud cost visibility and performance insights. Collaborate with Engineering and Finance stakeholders to implement automation and cost-aware decision-making tools.
You will lead the development and optimization of efficient data pipelines between Snowflake and Google Cloud Platform. Responsibilities include implementing native orchestration, config-driven processing, and ensuring robust data governance and observability.
You will develop and implement Snowflake-based data governance and privacy solutions, including PII discovery and automated remediation workflows. Additionally, you will build and maintain ETL/ELT pipelines while collaborating with cross-functional teams to ensure data quality and compliance.
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