We are looking for a highly skilled Senior Data Engineer to join our team. In this role, you will play a key part in designing, building and maintaining our data platform and the data-driven systems that power reporting and analytics across the company.

This is a hands-on role where you will contribute to technical decisions, collaborate closely with the team and help improve our data ecosystem. You will work across data engineering and analytics-enablement use cases, helping transform raw operational data into clean, reliable, business-ready data that decision-makers can trust.

Responsibilities

- Design, build and maintain scalable and reliable data pipelines and infrastructure on Google Cloud Platform (GCP).
- Develop and optimize ETL/ELT processes using Cloud Composer (Airflow) and Dataflow to ingest, transform and load data efficiently (incremental/delta loads via change-tracking/CDC patterns, plus full bulk-refresh patterns).
- Model and maintain the data warehouse on BigQuery, authoring and optimizing views, scheduled queries, stored procedures and UDFs across the ingestion, transformation and reporting datasets.
- Write production-ready SQL (BigQuery Standard SQL) and Python to support data workflows, transformations and automation.
- Own the CI/CD for the warehouse: dataset/table schema-as-code (e.g. Terraform or Dataform), BigQuery deployment pipelines, GitHub Actions workflows, and least-privilege Workload Identity Federation/IAM service accounts for deploys.
- Own the reporting-layer publish automation/CI (Python + GitHub Actions) and the BigQuery views/LookML that feed reporting, partnering with the BI Analyst who drives requirements and validates output.
- Ensure data quality, accuracy and consistency through validation, monitoring (e.g. Cloud Monitoring/Logging, dbt tests or similar)



and testing practices.
- Collaborate with engineers, analysts and business stakeholders to translate business requirements into scalable technical solutions.
- Participate in code reviews and contribute to technical discussions and improvements.
- Support and share knowledge with other engineers in the team.
- Stay up to date with new technologies and best practices to continuously improve the data platform.

Technology Requirements

- 5+ years of professional experience in data engineering or related roles. We are versátil for candidates with strong recent experience in cloud data pipelines and cloud data warehousing.
- Strong experience with GCP services, especially BigQuery, Cloud Composer (Airflow)/Dataflow, and Cloud Functions.
- Advanced SQL skills (query authoring, stored procedures/UDFs, performance and cost tuning in BigQuery).
- Experience with dimensional modeling and building/maintaining a data warehouse.
- Production experience writing Python for automation and CI/CD tooling.
- Experience with Git and collaborative development workflows, including GitHub Actions.
- Familiarity with database DevOps (schema-as-code via Terraform or Dataform, automated BigQuery deployments) and secure cloud auth (IAM, Workload Identity Federation) is a strong plus.
- Experience with BI tools — especially Looker (LookML modeling, Looker instance administration) — is a plus.
- Awareness of legacy ETL/OLAP technologies is a plus, as some legacy components are still being migrated.

Profile Requirements

- Strong problem-solving and technical skills.
- Ability to work independently while collaborating effectively with a team.
- Comfortable working on complex problems with a hands-on approach.
- Good communication skills and ability to work cross-functionally.
- Proactive and adaptable in evolving environments.

📌 Data Engineer (Argentina)
🏢 Prosigliere
📍 Argentina