Data Platform Engineer (Python, GCP, Airflow & Terraform) Level III - Mexico Only
Indexed description
- Design, evolve, and maintain scalable data orchestration platforms that simplify ETL/ELT operations and abstract the complexities of big data technologies.
- Build and maintain self-service platform capabilities for engineers, data scientists, and analysts.
- Develop and maintain integrations with diverse data sources and destinations, including Kafka, GCS, BigQuery, Postgres, and S3, supporting both batch and real-time processing.
- Provision and manage cloud data infrastructure using Terraform, leveraging automated and version-controlled Infrastructure as Code pipelines.
- Build, maintain, and orchestrate reliable data pipelines using Airflow and Kubernetes.
- Develop platform tooling, automation, services, and CLIs using Python.
- Build and operate metadata management, data cataloging, governance, and data-lineage capabilities to make enterprise data discoverable and trustworthy.
- Design scalable and resilient solutions capable of handling large data volumes, high velocity, and diverse data formats.
- Apply modern CI/CD and Git-based workflows to platform and data pipeline delivery.
- Evaluate and incorporate emerging big data, ETL, and AI-assisted development technologies where appropriate.
- Create and maintain comprehensive technical and user documentation for platform capabilities and workflows.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
- 5–7 years of professional experience in Data Engineering, Data Platform Engineering, or related software engineering roles.
- Strong professional programming experience with Python, including building and maintaining automation, services, and/or command-line tools.
- Strong proficiency in SQL, particularly within modern cloud data environments such as BigQuery.
- Hands-on experience designing and maintaining ETL/ELT pipelines and a solid understanding of modern data pipeline architecture.
- Experience with modern data transformation frameworks such as dbt.
- Strong hands-on experience with Google Cloud Platform (GCP) data technologies, particularly BigQuery, GCS, and Dataproc Serverless.
- Strong experience with Infrastructure as Code (IaC), particularly Terraform, for provisioning and managing cloud data infrastructure.
- Hands-on experience building and orchestrating data pipelines using Apache Airflow.
- Experience working with Kubernetes in data platform or cloud environments.
- Experience with streaming and event-driven data technologies such as Kafka / Confluent Cloud.
- Working knowledge of data governance, metadata management, data cataloging, and data lineage concepts.
- Familiarity with CI/CD and Git-based development workflows, including tools such as GitHub Actions.
- Experience using AI-assisted developer tooling, including LLMs, Model Context Protocol (MCP), and/or copilot-style productivity tools.
- Excellent problem-solving and communication skills, with the ability to collaborate effectively across engineering and business teams.
- Experience with AWS data and cloud technologies.
- Hands-on experience with metadata, data cataloging, or data-lineage platforms such as DataHub, Collibra, Amundsen, or similar tools.
- Experience with BI or semantic-layer technologies such as Looker / LookML.
- Experience with data quality, observability, SLOs, error budgets, and production/on-call operations for data platforms.
- Familiarity with distributed data processing frameworks such as Apache Spark.
- Experience with Java and/or Scala is a plus.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit https://www.linkedin.com/company/confiz/
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