Engenheiro de Dados Sênior — Governança, Catálogo e FinOps (GCP)
New
J
JobgetherData engineering
Based in BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLCI/CDBigQuery
Requirements
- Strong professional experience in data engineering and data governance on GCP, particularly with BigQuery and Dataplex.
- Knowledge of the current Dataplex Catalog architecture, Aspect Types, and Entry Groups.
- Advanced proficiency in Python and SQL for automation, auditing, and metadata pipeline development.
- Knowledge of BigQuery INFORMATION_SCHEMA, Cloud Audit Logs, BigQueryAuditMetadata, Cloud Billing, and GCP APIs, including the Looker Studio API.
- Hands-on experience with FinOps and BigQuery cost optimization, including On-Demand pricing, Editions/Slots, Logical and Physical Storage, Time Travel, partitioning, and clustering.
- Understanding of data security and privacy practices, including Cloud IAM, Policy Tags, CLS, RLS, dynamic masking, and LGPD compliance.
- Experience defining and implementing Data Contracts, YAML/JSON Schema, schema evolution practices, and CI/CD validation processes.
- Understanding of performance and caching implications associated with BigQuery security policies.
- Strong analytical and problem-solving skills to translate governance and cost-management needs into practical technical solutions.
- Nice to have: experience with Cloud DLP, automated sensitive-data classification, Dataform/dbt, LLMs, AI agents, or automated data cataloging and documentation.
- Nice to have: FinOps Certified Practitioner or Google Cloud Professional Cloud Security/Data Engineer certification, and familiarity with ODCS or Data Contract Specification.
Responsibilities
- Implement and improve GCP data governance capabilities using Dataplex Catalog, Aspect Types, Entry Groups, Business Glossary, Data Lineage, and Data Profiling.
- Develop automated metadata collection, cataloging, and enrichment processes using Python, SQL, Dataform/dbt, APIs, and AI/LLMs.
- Map Looker Studio dashboards and data sources.
- Monitor and optimize BigQuery costs by analyzing jobs, storage, reservations, and unused tables using INFORMATION_SCHEMA and Cloud Billing.
- Automate FinOps policies for cost labeling, consumption alerts, quotas, maximum_bytes_billed controls, and table archiving or deletion.
- Automate BigQuery security and privacy policies using Cloud IAM, Policy Tags, CLS, RLS, dynamic masking, and Cloud DLP.
- Define Data Contracts, YAML/JSON schemas, and schema evolution rules, and integrate validations into CI/CD pipelines.
- Develop dashboards and indicators for data governance, cloud costs, and Data Lake health.
- Provide technical and consultative guidance to engineering teams and business stakeholders on governance, security, and cost optimization.
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