Senior Data Engineer, AI and Databricks
RevStar
Build cloud-agnostic Databricks Lakehouse pipelines and production AI solutions for RevStar clients. Improve Spark performance, MLOps, governance, and automated deployments.
Open
Keyrus is an international data and consulting company that helps organizations turn data into insight and informed action. Its work spans data analytics, data advisory, and data management, with vendor-independent approaches tailored to different business needs. Operating across 18 countries, Keyrus brings together teams focused on analytical expertise, collaboration, and practical innovation. Employees can continue developing their skills through the company’s KLX learning platform while contributing to projects shaped by an open, inclusive, and transparent workplace culture.
Google Cloud Data Engineer – Colombia Remote
Build scalable Google Cloud data pipelines for Keyrus enterprise intelligence solutions. Work with BigQuery, Pub/Sub, Dataform, Cloud Storage, and Cloud Composer.
Description
- Create and maintain scalable data ingestion pipelines and workflows on Google Cloud Platform.
- Build and optimize data processing and transformation solutions with BigQuery, Dataform, Pub/Sub, Cloud Storage, and Cloud Composer.
- Write SQL queries to extract, transform, validate, and troubleshoot data across enterprise systems.
- Integrate data from multiple sources into BigQuery through reliable ingestion processes.
- Resolve pipeline failures, data inconsistencies, and production issues to keep operations stable.
- Develop and run unit, system, integration, and user acceptance tests; document results and verify solution quality.
- Work with engineers, architects, and business stakeholders to turn requirements into effective technical solutions.
- Contribute to technical design, code reviews, project planning, and ongoing improvements.
- Create and update technical documentation, development specifications, and implementation plans.
- Apply security, data governance, and engineering standards when handling sensitive information.
- Join the production support on-call rotation, typically covering one full week every four to six weeks.
Requirements
- At least three years of professional experience in data engineering, data integration, or a related technical role.
- Bachelor’s degree in computer science, information technology, engineering, or a related field.
- Experience designing, building, and maintaining cloud-based data ingestion pipelines.
- Experience implementing and supporting data processing workflows on Google Cloud Platform.
- Experience diagnosing production data pipelines and resolving data quality or integration issues.
- Familiarity with software development practices, testing approaches, and technical documentation.
- Ability to work independently and collaborate effectively with technical teams and business stakeholders.
- Hands-on experience using Google Pub/Sub for event-driven messaging and data ingestion.
- Strong BigQuery skills for data warehousing, querying, and processing.
- Experience using Google Dataform for SQL-based transformations and workflow management.
- Experience building processes to ingest data from multiple sources into BigQuery.
- Experience with Google Cloud Storage for cloud storage and data integration.
- Knowledge of Cloud Composer (Apache Airflow) for workflow orchestration and scheduling.
- Experience using GitHub for version control and team development.
- Strong SQL skills for querying, transforming, validating, and troubleshooting data.
- Experience with Google Cloud Data Fusion.
- Experience connecting to relational databases such as SQL Server, DB2, or Oracle.
- Experience integrating REST APIs and SOAP web services.
- Familiarity with other Google Cloud services, databases, and enterprise integrations.
- Experience using Jira and Confluence for project tracking and documentation.
- Previous experience in the retail industry.
- Must be based in Colombia and available to work Eastern Time hours.
Benefits
- Mandatory Colombian employment benefits and statutory entitlements under applicable labor law.
- Fully remote work aligned with Eastern Time hours.
- Opportunities for professional development, collaboration, and ongoing learning.
- A stimulating workplace with opportunities to take on challenges and explore new horizons.
- A workplace culture centered on innovation and entrepreneurship.
- Work on enterprise-scale data engineering projects using modern cloud technologies.
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