Jobs in Portugal, in English.

Data Analyst

Remote in Portugal·Full-time·Added 2 days ago (last checked 23 Oct)

AgileEngine

23 open roles

Apply

Our summary

Work mode: Remote (Portugal)
Contract: Full-time
Experience: 4+ years

Skills

Requirements

What we're looking for

The mandatory requirements are advanced SQL, experience building ETL/ELT pipelines with PySpark, Databricks, or Snowflake, 4+ years in data analytics, experience with large-scale IT infrastructure or asset datasets, Power BI, Tableau, or Qlik, hands-on use of GenAI tools, and strong English communication skills.

At least 4 years in Data Analytics, with strong quantitative and qualitative analytical skills and a proven track record of solving complex data problems.
ETL/ELT Processing: Robust experience building ETL/ELT pipelines, ideally utilizing a PySpark / Databricks / Snowflake stack (or equivalent modern cloud technologies).
Advanced SQL: Strong, production-grade SQL skills for complex querying, data joining, and analytical operations across large-scale systems.
Large-Scale Asset & Infrastructure Datasets: Hands-on experience working with massive, enterprise-grade datasets related to IT infrastructure, hardware/software assets, network configurations, or cloud resources.
Dashboarding & Business Intelligence: Proficient in creating interactive dashboards using Power BI (or similar tools such as Tableau/Qlik) to translate data into business narratives.
Communication: Excellent oral and written communication skills, with the ability to lead data-focused discussions and customer-facing interactions independently.
Frontier AI Technologies: Practical knowledge of and experience using cutting-edge AI technologies, Generative AI tools, and LLM framework integrations.
Upper-intermediate English level.

Nice to have

ServiceNow & CMDB: Hands-on experience with ServiceNow data models, Configuration Management Databases (CMDB), or ServiceNow development experience is a huge plus.
Authoritative Data Source (ADS) Strategy: Experience designing or maintaining strategies for enterprise authoritative data sources.
Data Governance & Risk Management: Knowledge of enterprise data governance frameworks, compliance standards, internal audit protocols, and risk management processes.
Data Transformation Expertise: Demonstrated expertise in end-to-end data mapping, complex transformations, and normalization across disparate datasets.

Pay & benefits

What you'll get

Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
Well-being & support: access local well-being programs and people-focused support tailored to your location

The role

We are looking for a Data Analyst to analyze and visualize large-scale IT infrastructure and asset data, building pipelines and dashboards for internal stakeholders.

What you'll do

Data Analysis & Visualization: Design, build, and maintain interactive Power BI (or equivalent) dashboards to deliver clear metrics on enterprise infrastructure, assets, and operational risks.
ETL/ELT Data Engineering: Develop, optimize, and maintain robust data transformation pipelines processing massive volumes of asset and infrastructure data.
Stakeholder & Client Leadership: Directly engage with customers, business partners, and engineering teams to identify requirements, translate business needs into data solutions, and independently resolve complex data challenges.
Data Querying & Modeling: Write complex, optimized SQL queries to manipulate, validate, and extract key insights from multi-source large-scale databases.
AI & Automation Integration: Evaluate and leverage frontier AI tools and technologies to improve data processing workflows, analytical modeling, and operational efficiency.
Data Quality & Governance: Assist in defining data mappings, transformations, and schema normalizations to maintain high standards of data integrity.