Arquiteto de Dados Sênior (GCP e Databricks)
New
J
JobgetherData Architecture
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- More than 5 years of experience in scalable Data Governance; More than 5 years of hands-on experience with the Google Cloud Platform ecosystem.
- Required Skills
- PythonSQLGCPData modelingBigQueryDatabricksPySpark
Requirements
- More than 5 years of experience in scalable Data Governance.
- More than 5 years of hands-on experience with the Google Cloud Platform ecosystem, including BigQuery, Cloud Storage, Dataflow, Cloud Composer, and Dataplex.
- Deep understanding of data modeling concepts, Data Mesh principles, and architectures supporting distributed data ownership.
- Experience with Apache Iceberg, Open Table Format concepts, Apache Spark, and BigLake.
- Strong practical experience with Databricks, including Delta Lake, Unity Catalog, and cluster optimization.
- Proven experience leading structured and unstructured data migration projects.
- Solid professional background as a Data Architect or Principal/Senior Data Engineer.
- Advanced proficiency in PySpark, Python, and SQL.
- Experience with Lakehouse architecture, CI/CD pipelines, and DataOps practices.
- Excellent communication and stakeholder management skills.
- Availability to work remotely under a CLT employment model.
Responsibilities
- Lead the design, documentation, and implementation of modern and scalable data architectures, particularly Lakehouse environments built with Google Cloud Platform and Databricks.
- Drive complex data migration initiatives, including transitions from on-premise environments to the cloud and migrations between cloud platforms.
- Define standards and best practices for data ingestion, processing, and consumption, balancing performance, scalability, reliability, and infrastructure costs through FinOps principles.
- Establish and promote effective data modeling practices across dimensional, relational, and NoSQL approaches, as well as Medallion Architecture principles.
- Define and strengthen Data Governance guidelines covering data quality, lineage, cataloging, security, access, and compliance with LGPD requirements.
- Act as a senior technical reference for Data Engineering and Data Science teams, supporting complex architectural decisions.
- Promote a strong data culture by mentoring junior professionals, sharing knowledge, and contributing to the continuous evolution of data engineering practices.
- Partner with business stakeholders and organizational leaders to translate business requirements into secure, scalable, and technically sound data solutions.
- Establish and improve data delivery practices, including CI/CD and DataOps processes.
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