data analytics intern (pasantía).

detalles del trabajo

detalles del trabajo

As a Data Modeler Intern, you will be expected to perform the following activities in alignment with your experience level:

Gather, understand, and document functional and non-functional requirements from stakeholders to support analytical solutions

  • Write or collaborate on the creation of business requirements documents (BRDs) detailing solution characteristics, business expectations, and anticipated value.
  • Create diagrams that illustrate high-level data domains and key concepts involved in solution design.
  • Document required measures and KPIs to support business objectives, including clear definitions and calculation logic.

Explore and understand data assets to be leveraged as sources for analytical solutions

  • Build and maintain detailed inventories of data assets required to deliver analytical solutions.
  • Profile data assets to understand their granularity, domain context, business meaning, definitions, data quality characteristics, and interrelationships.

Design solution architecture to consume, transform, and deliver data for analytical solutions – Data Marts / Data Lake

  • Design scalable and reusable logical data models for analytical repositories using relational and dimensional modeling techniques, integrating and conforming data from multiple sources.
  • Document entities, attributes, and relationships using logical data model diagrams.
  • Define detailed data movement requirements to populate modeled entities, including column mappings, joins, load strategies, and load dependencies.
  • Perform internal testing and system integration testing (SIT) on developed data assets.
  • Collaborate with cross-functional teams to deliver end-to-end analytical solutions, including:
    • Data Governance teams for integration of master and reference data
    • Data Services / Engineering teams for ETL development
    • Business stakeholders for user acceptance testing (UAT)
    • Data Quality teams to support periodic data quality assessments
    • Report and dashboard developers, acting as a subject-matter expert (SME) on the designed data assets
    • Production Support teams for troubleshooting and issue resolution

Implement data assets for serving data – Semantic Layer

  • Design and implement semantic-layer data assets to support reports, dashboards, self-service analytics, and other downstream consumption scenarios.
  • Create and maintain data dictionaries and documentation to enable and empower data consumers.

Demonstrate a solution-owner mindset

  • Collaborate in backlog refinement, maintenance, and prioritization activities.
  • Actively participate in agile ceremonies, contributing to discussions on current work, next steps, dependencies, and risks.
  • Provide work breakdowns, effort estimates, and expected delivery timelines for assigned tasks.

Build and support diverse, high-performing teams

  • Work effectively with a high degree of independence in a remote or hybrid environment.
  • Continuously expand professional value by learning emerging technologies and concepts and applying them to improve existing products, processes, and outcomes.

Required Qualifications – Experience, Skills, and Knowledge

  • Completion of at least the 2nd year and current enrollment in the 3rd or 4th year of an undergraduate program in Mathematics, Computer Science, Statistics, Business Management, Information Systems, or a related field
  • English proficiency at an advanced level (C1 or equivalent)
  • SQL: basic data querying (DQL) skills
  • Power BI: basic experience with report development or semantic model creation

Preferred Qualifications

  • Familiarity with Data Warehouses, Data Lakes, or Data Lakehouse architectures
  • Knowledge of relational and dimensional data modeling techniques
  • Exposure to agile methodologies such as SCRUM and tools like Azure DevOps
  • Awareness of cloud computing platforms such as Azure, Google Cloud, or Amazon Web Services, including Databricks
  • Interest or foundational knowledge in AI concepts, including prompting techniques or agent development
  • Exposure to Microsoft Fabric
Nos esforzamos todos los días en crear un entorno diverso y nos enorgullece ser una empresa con igualdad de oportunidades para todas las personas, independientemente de su raza, color, religión, sexo, identidad sexual u orientación sexual, país de origen, genética, discapacidad o edad.

As a Data Modeler Intern, you will be expected to perform the following activities in alignment with your experience level:

Gather, understand, and document functional and non-functional requirements from stakeholders to support analytical solutions

  • Write or collaborate on the creation of business requirements documents (BRDs) detailing solution characteristics, business expectations, and anticipated value.
  • Create diagrams that illustrate high-level data domains and key concepts involved in solution design.
  • Document required measures and KPIs to support business objectives, including clear definitions and calculation logic.

Explore and understand data assets to be leveraged as sources for analytical solutions

  • Build and maintain detailed inventories of data assets required to deliver analytical solutions.
  • Profile data assets to understand their granularity, domain context, business meaning, definitions, data quality characteristics, and interrelationships.

Design solution architecture to consume, transform, and deliver data for analytical solutions – Data Marts / Data Lake

  • Design scalable and reusable logical data models for analytical repositories using relational and dimensional modeling techniques, integrating and conforming data from multiple sources.
  • Document entities, attributes, and relationships using logical data model diagrams.
  • Define detailed data movement requirements to populate modeled entities, including column mappings, joins, load strategies, and load dependencies.
  • Perform internal testing and system integration testing (SIT) on developed data assets.
  • Collaborate with cross-functional teams to deliver end-to-end analytical solutions, including:
    • Data Governance teams for integration of master and reference data
    • Data Services / Engineering teams for ETL development
    • Business stakeholders for user acceptance testing (UAT)
    • Data Quality teams to support periodic data quality assessments
    • Report and dashboard developers, acting as a subject-matter expert (SME) on the designed data assets
    • Production Support teams for troubleshooting and issue resolution

Implement data assets for serving data – Semantic Layer

  • Design and implement semantic-layer data assets to support reports, dashboards, self-service analytics, and other downstream consumption scenarios.
  • Create and maintain data dictionaries and documentation to enable and empower data consumers.

Demonstrate a solution-owner mindset

  • Collaborate in backlog refinement, maintenance, and prioritization activities.
  • Actively participate in agile ceremonies, contributing to discussions on current work, next steps, dependencies, and risks.
  • Provide work breakdowns, effort estimates, and expected delivery timelines for assigned tasks.

Build and support diverse, high-performing teams

  • Work effectively with a high degree of independence in a remote or hybrid environment.
  • Continuously expand professional value by learning emerging technologies and concepts and applying them to improve existing products, processes, and outcomes.

Required Qualifications – Experience, Skills, and Knowledge

  • Completion of at least the 2nd year and current enrollment in the 3rd or 4th year of an undergraduate program in Mathematics, Computer Science, Statistics, Business Management, Information Systems, or a related field
  • English proficiency at an advanced level (C1 or equivalent)
  • SQL: basic data querying (DQL) skills
  • Power BI: basic experience with report development or semantic model creation

Preferred Qualifications

  • Familiarity with Data Warehouses, Data Lakes, or Data Lakehouse architectures
  • Knowledge of relational and dimensional data modeling techniques
  • Exposure to agile methodologies such as SCRUM and tools like Azure DevOps
  • Awareness of cloud computing platforms such as Azure, Google Cloud, or Amazon Web Services, including Databricks
  • Interest or foundational knowledge in AI concepts, including prompting techniques or agent development
  • Exposure to Microsoft Fabric
Nos esforzamos todos los días en crear un entorno diverso y nos enorgullece ser una empresa con igualdad de oportunidades para todas las personas, independientemente de su raza, color, religión, sexo, identidad sexual u orientación sexual, país de origen, genética, discapacidad o edad.

resumen

  • número de referencia
    116553

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