Data Platform Engineer

CONSULTFIZ LATAM, a fully owned subsidiary of Confiz LLC, is looking for a Data Platform Engineer with strong experience in Python, GCP, Airflow, and Terraform to design, develop, and maintain scalable data orchestration platforms and self-service solutions. The ideal candidate will have hands‐on experience with ETL/ELT pipelines, cloud data infrastructure, data orchestration, streaming technologies, and Infrastructure as Code (IaC) . 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.
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 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.
We have a global team of amazing individuals working on highly innovative enterprise projects & products. People who work with us work with cutting‐edge technologies while contributing success to the company as well as to themselves.