Senior Data Architect / Engineer

Alcor; México; Remoto; MXN 2.235.000 - 2.980.000; Tempo pieno

Descrizione del lavoro

Alcor is seeking a senior Data Architect/Engineer to lead the design and delivery of an analytical data platform in Microsoft Fabric on a remote, LATAM-facing engagement. You will own end-to-end delivery, aligning architecture with governance and security requirements.

Responsibilities include building scalable data pipelines, modeling data, and enabling secure analytics for internal and customer-facing reporting while transferring knowledge to the client’s Data & Analytics team.

Competenze

• Senior-level experience delivering data architecture and data-engineering solutions in production environments.
• Proven ability to transform OLTP data into analytic platforms (data warehouses, lakehouses, OLAP).
• Strong hands-on experience in Azure data tools and Microsoft Fabric.
• Experience designing medallion or layered architectures and secure analytic patterns.

Mansioni

• Lead end-to-end technical delivery across internal teams and external partners.
• Design and implement data pipelines and analytical models on Microsoft Fabric in Azure.
• Ensure data security, governance, and role-based access for analytic consumption.

Conoscenze

SQL

Python

PySpark

Azure

Data modeling

Strumenti

Microsoft Fabric

Azure

Descrizione del lavoro

Contract Duration: 12 months
Engagement: Full-time contract
Location: Remote, Mexico, Colombia, Argentina

Project Objective

Our client is looking for a senior, hands-on Data Architect / Engineer to lead the design and delivery of an analytical data platform in Microsoft Fabric.

The objective is to offload historical and analytical workloads from a core transactional product into a secure, governed analytical data store. The solution must preserve the authorization context required for downstream consumption, support customer-facing reporting, and establish a foundation for future data products.

You will own the technical delivery of this initiative, working with internal teams and external technical partners from discovery and architecture through implementation, production readiness, documentation, and knowledge transfer.

Key Outcomes

• Deliver a production-ready architecture that separates transactional and analytical workloads.

• Design and implement ingestion and historical offload from Azure-based transactional databases into Microsoft Fabric.

• Establish a layered or medallion architecture covering source-aligned, transformed, and consumption-ready data.

• Create analytical and semantic models that support secure downstream reporting and customer-facing use cases.

• Understand the application's roles, permissions, and visibility rules, and translate the required authorization context into appropriate analytical access patterns.

• Design for historical preservation, change handling, retention, deletions, reconciliation, and future transactional data purging.

• Implement the engineering controls required for production operation, including testing, data quality, monitoring, recovery, security, and deployment.

• Assess the existing ingestion and analytical processes, retaining what works and improving or replacing what does not.

• Maintain clear technical documentation, architecture decisions, operational runbooks, and implementation knowledge throughout the engagement.

• Transfer knowledge to the internal Data & Analytics team so the platform can be operated and extended after the contract.

Required Experience

• Senior-level experience delivering data architecture and data-engineering solutions in production environments.

• Proven experience transforming data from complex OLTP applications into analytical platforms, data warehouses, lakehouses, or OLAP solutions.

• Strong hands-on experience building data solutions in Azure, with practical experience or working knowledge of Microsoft Fabric.

• Experience designing layered or medallion data architectures, analytical models, semantic layers, and downstream consumption patterns.

• Strong understanding of historical data offload and lifecycle management, including incremental change, deletions, retention, archival, reconciliation, and purge considerations.

• Experience designing secure analytical solutions based on application roles, permissions, tenant boundaries, and access‑control requirements.

• Experience with both single-tenant and multi-tenant data environments.

• Advanced SQL and strong hands‑on Python skills for building maintainable, testable, production‑ready data pipelines and transformations.

• Experience with PySpark or comparable distributed data‑processing frameworks.

• Ability to work across architecture and implementation, independently solve complex problems, and translate decisions into working solutions.

• Experience leading technical delivery across internal teams and external partners.

• Practical use of AI‑assisted engineering tools for technical discovery, development, testing, troubleshooting, and documentation, with appropriate review and validation of outputs.

• Strong written and spoken English.

Engagement Expectations

You will act as the primary technical owner for the assigned project scope. Success requires hands‑on delivery, proactive identification of technical risks, clear communication of decisions and trade‑offs, and close collaboration with Data & Analytics, Engineering, Product, Architecture, Security, and external delivery partners.

The engagement is expected to produce a working, supportable solution, not only an architecture recommendation or proof of concept.