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Digitais. Humanos. Transformadores.
Data Architect Specialist
Location
Brazil
Posted
64 days ago
Salary
0
Seniority
Senior
Job Description
Data Architect Specialist
Runtalent
• Design and evolve C&A's enterprise data architecture in a hybrid, multi-cloud environment (on-premises ↔ AWS ↔ Azure ↔ GCP). • Develop data extraction, ingestion, and transformation across the layers of the data lake to be built. • Design integrations between legacy systems and cloud ingestion and processing layers. • Define integration standards between local data centers, on-premises systems, and cloud solutions. • Ensure the architecture is resilient, secure, high-performing, and cost-optimized. • Architect large-scale data pipelines distributed across AWS, Azure, and GCP. • Define and maintain data lifecycles across Bronze, Silver, and Gold layers. • Implement Data Governance, Data Quality policies, and a unified catalog (Lake Formation, Glue Catalog, DataHub, Collibra, or equivalent). • Work with Product, Customer, and Supplier teams to define domains and enterprise models. • Integrate analytics consumption and data science environments across clouds. • Build architectures for real-time and batch consumption. • Guide engineering, analytics, and systems squads in adopting unified architecture patterns for the multi-cloud ecosystem. • Lead POCs, potentially comparative, across AWS, GCP, and Azure. • Support development of data extraction and ingestion.
Job Requirements
- Strong experience with hybrid integration: on-premises, AWS, GCP, and Azure.
- Hands-on experience with corporate connectivity.
- Experience designing multi-cloud architectures with standardization and interoperability.
- Deep knowledge of multi-cloud data pipelines: AWS (Kinesis, Glue, S3, Lake Formation, Redshift, EMR, Lambda); GCP (BigQuery, Dataflow/Beam, Pub/Sub, Composer); Azure (Data Factory, Synapse, ADLS, Databricks, Event Hub).
- Terraform.
- Deployment pipelines.
- Experience with ingestion patterns: CDC, streaming, batch, API ingestion, file ingestion.
- Data modeling: conceptual, logical, physical, canonical models, corporate standards.
- Big Data and distributed processing (Spark, EMR, Databricks desirable).
- Governance, metadata, quality, catalog, and lineage.
- Security and IAM.
- Orchestration tools: Step Functions, Airflow, MuleSoft.
- Data governance, metadata, Data Quality, lineage, and enterprise catalog.
- Experience with DW/BI (Power BI (Required), Looker (Preferred), Tableau (Preferred), QuickSight (Preferred)).
- Solid knowledge of messaging systems (Kafka, Pub/Sub, Event Hub, Kinesis).
- Experience with BI and self-service analytics (Power BI, Tableau, Looker).
- Experience with CI/CD, Infrastructure as Code (Terraform preferred), GitOps.
- Cloud security.
- Hands-on profile to support the development of data extraction and ingestion.
Benefits
- Remote work
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