Data Engineer Architect

Responsibilities

• End-to-End Solutions: You will design and develop end-to-end solutions for processing large data volumes, spanning from the initial business problem to scalable and optimized ETL/ELT pipelines.
• Tech Stack: You will work with technologies such as Databricks, Snowflake, dbt, and Microsoft Fabric , using Spark (Python/Scala) , SQL ; and orchestration with Airflow, Data Factory or similar tools.
• Advanced Architectures: You will help to define and implement advanced architectures under the Data Lakehouse and Data Warehouse paradigms, supporting diverse data processing patterns including Batch, Near Real Time, and Streaming .
• Data Integration: You will develop data ingestion and transformation pipelines from diverse sources (APIs, files, databases, streaming), to build analytical data models supporting business use cases.
• Platform Foundation : You will collaborate in the implementation of frameworks and engines that provide a standard framework for the main functions of a data platform: Orchestration, Ingestion, Transformation, Quality, Security, Testing, Deployment, Observability , among others.
• Collaboration: You will collaborate with multidisciplinary teams and stakeholders, translating complex requirements into efficient technical solutions.
• Continuous Learning: You will stay up to date with the latest technological trends—especially in Data & Analytics—through continuous training and the exploration of new tools and innovations.
• Career Path : You will be in control of your professional development together with your managers. SDG Group will give you the opportunity to build a professional career oriented to become a Data Architect in a world-class organization.

Requirement

• Education : Degree in Computer Engineering or Computer Science. It’s a plus to have a Master’s Degree in any Data-related field
• Languages : English C1 level or higher
• Experience : 2-3 year s of experience in Data Lake and/or Data Warehous e projects
• ETL/ELT : Experience on data integration with Spark (Python or Scala) and/or SQ L and dimensional data modelin g
• Cloud : Experience working in Cloud environments (AWS, GCP, or Azur e) and platforms (Databricks, Snowflake, Microsoft Fabri c)
• Code Management & DataOps : Solid understanding of Git, CI/CD, pipeline monitoring, data quality control, and data versioning
• Consulting Background : Previous experience in consulting is a plus

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