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Engineering Portfolio

Guillermo Garay

Data Engineer

Data Architecture · Analytics & BI · Digital product

I move data from SAP HANA into Microsoft Fabric and leave it modeled and ready for Power BI, designing incremental loads and traceability.

I also build digital products, and I like working end to end, from architecture to user experience.

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02 / experience

Career

Four years in data, BI, and digital transformation in retail. The technical detail of each piece of work lives in the cases.

  1. 2023 – present

    Semi-Senior Data Analyst

    Retail company

    Designed the Lakehouse + Warehouse architecture in Microsoft Fabric and led the Data Warehouse migration from SAP Datasphere / BW Bridge. I integrate sources such as SAP, Dynamics 365, and Salesforce, and build Power BI solutions.

  2. 2022 – 2023

    Cloud Applications Administrator

    Retail company

    Automated processes with Power Automate, migrated internal applications to Power Apps, and built Power BI dashboards for management.

  3. 2020 – 2022

    Technical Support

    Retail company

    Preventive and corrective maintenance of IT infrastructure (PCs, servers, networks, and CCTV) across multiple branches, plus hardware inventory control.

03 / cases

Technical case studies

Each case shows its architecture, the decisions made, and its limits. Finished work is kept apart from work still in development.

  • Data integration and modeling

    Documented case

    Enterprise Data Platform

    Data Warehouse migration from SAP Datasphere to Microsoft Fabric: integration from SAP HANA, Lakehouse and Warehouse layers, materialized tables, and models ready for Power BI.

    Flow from the ERP to analytical consumption
    1. SourceSAP HANA
    2. ExtractionFabric Pipelines
    3. StagingLakehouse
    4. WarehouseFabric Warehouse
    5. ConsumptionPower BI

    Outcome: −83%processing time: the refresh of critical business reports went from 30 to 5 minutes.

    • SAP HANA
    • SQL
    • Microsoft Fabric
    • Power BI

  • Orchestration and integration

    Documented case

    Data Pipeline Orchestration

    Python integrations between an ERP and external systems: master data snapshots, change detection, controlled delivery, and traceability for every run.

    Stages of an integration, from source to run log
    1. SourceSAP HANA · SQL
    2. SnapshotPython
    3. ChangesPython
    4. ValidationPython
    5. DeliveryHTTP
    6. Run logSQL · Fabric Warehouse

    Outcome: TODOE.g. runs per day or % of deliveries that succeed on retry.

    • Python
    • SQL
    • ETL
    • SAP HANA
    • Microsoft Fabric

  • Ecommerce for a client

    In development

    Sublime Ecommerce

    An online store for a sticker, sublimated T-shirt, DTF, and vinyl business: an admin-managed catalog, orders, custom orders with Custom Lab, and self-hosted deployment on a VPS.

    Infrastructure on the VPS
    1. DomainDNS
    2. ProxyTraefik
    3. AppNext.js · Docker
    4. DatabasePostgreSQL
    5. Backupsrclone · Drive

    Outcome: 298automated tests in the repository, over 18 versioned database migrations.

    • Next.js
    • TypeScript
    • PostgreSQL
    • Docker
    • Traefik

Cases anonymized for confidentiality.

04 / stack

Technology in context

No percentages or arbitrary levels: each technology appears next to the context I use it in.

Data Engineering

SQL
Extraction, transformation, and modeling on SAP HANA and Fabric Warehouse.
Python
System integrations and data process automation.
ETL / ELT
Full and incremental loads, staging, and materialization.

Data Platforms

SAP HANA
Source system: extraction queries over ERP tables.
Microsoft Fabric
Pipelines, Lakehouse, and Warehouse for staging and analytics.
BigQuery
Analytics architecture proposals.

Analytics

Power BI
Semantic models and reports connected to Fabric.
Data modeling
Grain, facts, and dimensions designed for consumption.
Data Warehousing
Staging and Warehouse layers, materialized tables.

Product Engineering

Next.js
App Router and Server Components in Sublime and this portfolio.
TypeScript
Strict mode and typed domain models.
React
Interface components with limited client state.
Tailwind CSS
Token-based visual systems.

05 / services

Areas of work

Topics I can help with, from diagnosis through implementation.

  1. Data Warehouse consulting

    Design of staging and Warehouse layers, table grain, and materialization strategy.

  2. Data integration and automation

    Pipelines between source systems and analytical destinations, with controls and traceability.

  3. SQL modeling and optimization

    Query and model reviews, incremental loads, and removal of unnecessary processing.

  4. Power BI solutions

    Semantic models, documented measures, and reports connected to a governed source.

  5. Data architecture

    Layers, flows, and responsibilities for a maintainable analytics platform.

  6. Digital product development

    Web applications with Next.js and TypeScript, from architecture to interface.

06 / contact

Let’s talk

Is your Power BI slow to refresh, or do you not trust the numbers? Write to me and we’ll look into it.

Email me

You can also find me on these channels.