Standort
Argentina, Argentinien
Arbeitsort
Vor Ort
Sprache
English
Veröffentlicht
21. Mai 2026
Zuletzt geprüft
30. Mai 2026
JobGrid-Kontext
Rollenübersicht von JobGrid
Data Engineer (Data Factory) at Allata: Argentina, Argentinien; Vor Ort. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Argentina, Argentinien, Vor Ort
- Source freshness: checked by JobGrid on 2026-05-30.
- Application path: candidates continue to the employer application page with non-personal referral tags.
Allata is a global consulting and technology services firm with offices in the US, India, and Argentina. We help organizations accelerate growth, drive innovation, and solve complex challenges by combining strategy, design, and advanced technology. Our expertise covers defining business vision, optimizing processes, and creating engaging digital experiences. We architect and modernize secure, scalable solutions using cloud platforms and top engineering practices.
Allata also empowers clients to unlock data value through analytics and visualization and leverages artificial intelligence to automate processes and enhance decision-making. Our agile, cross-functional teams work closely with clients, either integrating with their teams or providing independent guidance—to deliver measurable results and build lasting partnerships.
We are seeking a skilled Data Engineer to join our team and contribute to data-driven initiatives using a modern Microsoft data stack. This role focuses on designing, building, and optimizing scalable data solutions that support analytics, reporting, and business decision-making through Azure Data Factory, Microsoft Fabric, Power BI, SQL, and Python.
Role & Responsibilities:
- Design, develop, and maintain scalable data pipelines using Azure Data Factory, SQL, and Python.
- Build and optimize ETL/ELT processes across Microsoft-based cloud data platforms.
- Work with Microsoft Fabric to support modern analytics and data engineering workflows.
- Develop and maintain data models and transformation logic to support reporting and analytics needs.
- Collaborate with analysts, business stakeholders, and technical teams to translate business requirements into technical solutions.
- Support Power BI reporting needs by enabling clean, reliable, and well-structured datasets.
- Ensure data quality, consistency, and performance across ingestion, transformation, and reporting layers.
- Monitor and optimize workflows for reliability, scalability, and maintainability.
- Contribute to CI/CD, deployment, and operational best practices within the Microsoft ecosystem.
- Support data governance, documentation, and process improvement efforts.
Hard Skills - Must have:
- Strong hands-on experience with Azure Data Factory.
- Experience working with Microsoft Fabric and/or related Microsoft data platform technologies.
- Strong SQL skills, including query development, transformations, and performance optimization.
- Experience supporting reporting and analytics solutions through Power BI-ready datasets or semantic layers.
- Proficiency in Python for data engineering, automation, or transformation tasks.
- Solid understanding of ETL/ELT concepts, data integration, and data pipeline design.
- Experience working with relational databases such as SQL Server, Azure SQL, PostgreSQL, or similar.
- Knowledge of cloud-based data engineering practices within Azure environment.
Hard Skills - Nice to have/It's a plus:
- Experience with Microsoft Fabric workloads such as Data Factory, Lakehouse, Warehouse, or Dataflows.
- Experience with Power BI development, dashboarding, or performance tuning.
- Familiarity with data modeling concepts for analytics and reporting.
- Experience with CI/CD and DevOps practices in Azure-based environments.
- Exposure to data governance, security, and access management in Microsoft data platforms.
- Experience working in consulting environments or with distributed cross-functional teams.
Soft Skills / Business Specific Skills:
- Strong analytical and problem-solving skills.
- Ability to work effectively in cross-functional and distributed teams.
- Clear communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Proactive mindset with a strong sense of ownership.
- Commitment to delivering high-quality, reliable data solutions.