Minimum Requirements:Degree in computer science or telecommunications engineering, or any other degree in a technical environment with proximity to software engineeringAt least 4 years of experience in a data engineer role implementing data ingestion and transformation solutions with on-premise or cloud toolsExperience in data architecture (structure, partitioning, modeling, layering, and lifecycle) in data warehouse environmentsAdditionally, it will be important to have experience in some of the following tools:Languages: SQL, Python; Java knowledge is a plusExperience with some of the different data modeling paradigms: Kimball, Immon, Data Vault 2.0Knowledge of one of the data clouds: Snowflake, BigQuery, Redshift, etc.Knowledge of data integration tools such as dbt, Talend, etc.Knowledge of orchestration tools such as Apache AirflowKnowledge of code management methodologiesFamiliarity with terms such as DataOps, Data Observability, Data Mesh, etc.Previous consulting experience in the Data & Analytics worldTraining through a master's degree or other alternatives to increase your skills (for example, a master's degree in big data and analytics is highly valued)Knowledge in any of the following technologies: Databricks, AWS Glue, GCP Dataflow & Dataproc, etc.Knowledge with respect to containerization technologies and toolsExperience using cloud technologies with respect to concepts such as infrastructure enablement, automation of data pipelines, and operation and monitoring of data processing systemsSince we work in a global environment, it will be a plus if you can communicate in EnglishAbout the JobSDG Group is a global consulting firm focused exclusively on Data & Analytics solutions that cover the entire data value chain. SDG provides both consulting and specialization career plans for those who want to progress in the data world. Through our Smart Work culture, you can define the work model that best suits you and your personal needs, while also collaborating on high-impact initiatives for leading clients in their respective industries.As a data engineer in the Data Technologies area, you will be part of multidisciplinary teams with the goal of helping our clients address data initiatives in highly complex technical environments. You will be able to use a wide range of innovative technologies to build data management solutions under various processing and modeling paradigms, applying the right principles in terms of development and architecture.Thanks to our specialist path, you will have the opportunity to grow as an engineer and/or data architect. You will have access to tools and resources for your continuous learning and professional growth while you get involved in various challenges that allow both SDG Group and our customers to exploit the maximum value of their data.Responsibilities:Participate in the development of end-to-end data engineering solutions, from understanding the problem and business objectives, to the development of fully productive data systemsProvide technical input on the processes and architectures that are developed to feed into the technical conversations that take place during design phasesParticipate in requirements gathering for data architectures and pipelines; sometimes you will need to think about what modeling strategy to choose based on the sources and customer needs, while other times you will need to think about the strategy for ingesting sources with a metadata-driven engineAdditionally, you may also need to complete proof-of-concepts and tests with new technologies in the market and new cloud services that we believe may be useful for our projects or clientsSDG Group is a global consulting firm specialized in Data & Analytics. We are committed to unlocking organizations' potential and hidden value by offering in-depth analytics expertise that empowers our clients' business models to become successful data-driven enterprises. Innovation is in our DNA. We constantly innovate our value proposition with cutting-edge laboratories and transformational models to provide the ultimate analytics practices and solutions.
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