Data Architect

Що робити

Design end-to-end data architectures on Snowflake and/or Databricks, deployed on Azure and/or AWS: ingestion, storage, processing, serving and consumption layers.
Define lakehouse and data warehouse patterns (medallion architecture, data vault, dimensional models) and choose the right one for each use case.
Lead migrations from legacy platforms (on-prem DWH, Hadoop, Teradata, Oracle, SQL Server) to the cloud, including assessment, roadmap and cutover plan.
Set standards for data modelling, pipeline design, CI/CD, infrastructure as code and environment strategy.
Design data governance, security and compliance: access control, data lineage, cataloguing (Unity Catalog, Snowflake Horizon, Purview), GDPR and local LATAM privacy laws.

8+ years in data engineering or data platforms, including 3+ years as a Data or Solution Architect.
Hands-on production experience with Snowflake and/or Databricks (at least one in depth).
Strong knowledge of Azure and/or AWS data services, for example:
Azure: ADLS Gen2, Data Factory, Synapse/Fabric, Event Hubs, Purview, Key Vault
AWS: S3, Glue, Redshift, Kinesis, Lambda, Lake Formation, IAM

Certifications: SnowPro Advanced Architect, Databricks Certified Data Engineer Professional, Azure Solutions Architect Expert, AWS Solutions Architect Professional or AWS Data Analytics/Data Engineer.
Streaming architectures (Kafka, Spark Structured Streaming, Snowpipe Streaming, Delta Live Tables).
Data mesh, data products and data contracts in practice.
MLOps and GenAI data foundations (feature stores, vector search, RAG pipelines).
Domain experience in banking, insurance, retail, telecom or energy.

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