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 trendsespecially in Data & Analyticsthrough 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
sEducation: 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+ years of experience in Data Lake and/or Data Warehouse projects
.ETL/ELT: Experience on data integration with Spark (Python or Scala) and/or SQL and dimensional data modeling
.Cloud: Experience working in Cloud environments (AWS, GCP, or Azure) and platforms (Databricks, Snowflake, Microsoft Fabric)
.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
