Engineering Jobs in Lisbon, Portugal (Now Hiring) — 580 open — Page 26

About Zango

Zango AI is a leading AI start-up for financial services. We work with top ⅗ banks in Portugal and are backed by tier 1 investors.

Role Overview

We are hiring a Lead Data Engineer to act as the senior technical authority inside the Data & Analytics function. The role owns technical decisions across our internal data engineering team and the external delivery partners working alongside us.

This is a hands-on leadership role. You set the engineering standards, validate architecture proposals, manage delivery decisions day-to-day, and ensure the foundations we lay on Microsoft Fabric are scalable, cost-efficient and durable. The Data & Analytics platform is built on Microsoft Fabric and Azure. The team is building reusable data products that will underpin CRM, customer 360, omnichannel, analytics and regulatory reporting use cases across the bank.

Stakeholders

• Leads: Internal data engineering team

• Partners with:

  • External vendors

  • Internal architecture function - a separate team in the bank. Your role is to validate and challenge their proposals, then convert them to execution roadmaps.

  • Functional / business leads (CRM, marketing, regulatory reporting) - they own business stakeholder management; you own technical delivery confidence.

  • Data governance team - alignment partner on quality, lineage and regulatory reporting requirements.

What You Will Own

Technical leadership

• Validate data architecture proposals from the internal architecture team and external partners. Push back where there are gaps. Convert sound proposals into execution roadmaps with the team.

• Set engineering standards across the function, ingestion patterns, modelling approaches, orchestration, testing, deployment, and observability.

• Own technical decisions across multiple parallel programmes. Remove decision bottlenecks from the Head of Data & Analytics.

• Drive cost discipline as a first-class concern. Azure consumption costs are material; every design choice considers compute, storage and Fabric capacity cost implications.

Platform engineering

• Lead the design of batch, micro-batch and near real-time ingestion frameworks.

• Define data modelling approaches (dimensional, data vault, or hybrid) across conceptual, logical and physical layers.

• Build for reusability: build once, reuse many. Every data product should be designed to serve multiple downstream use cases.

• Ensure pipeline performance, reliability, data quality and operational readiness.

Team and vendor management

• Lead the internal data engineering team. Develop senior engineers into multipliers, raise the bar across the function, unblock people, run the engineering rhythm.

• Manage external delivery partners. Hold them to scope, deliverables, technical alignment with our standards, and commercial discipline.

• Identify capability gaps inside the team and put a plan in place to close them through hiring, upskilling or partner support.

Stakeholder engagement

• Work closely with the functional/business leads who handle direct business stakeholder relationships. You provide the technical confidence; they translate the demand.

• Align with the data governance function on data quality, lineage, classification and regulatory reporting.

Must Have

• 5+ years in data engineering, with 2+ years in a Lead.

• Demonstrated experience managing or leading data engineering team.

• Hands-on experience with Microsoft Fabric, or deep production experience with the Azure data stack (Databricks, Data Factory, Synapse, Data Lake) with clear evidence of Fabric adoption.

• Strong data modelling expertise, dimensional modelling, data vault, or modern equivalents, applied in production at enterprise scale.

• Track record building ETL/ELT, streaming and orchestration pipelines on the Microsoft data stack.

• Native Portuguese, fluent in written and spoken English.

Nice to Have

• Experience managing external delivery partners or consultancies, holding them to scope, deliverables and architectural alignment.

• Experience in regulated financial services (banking, insurance, asset management) with awareness of data governance and regulatory reporting constraints.

• Experience leading a legacy-to-cloud data warehouse migration end-to-end.

• Power BI proficiency (semantic model design, governance, performance).

• Strong working knowledge of Python, Spark, and modern orchestration tools (Airflow, ADF, Fabric Data Pipelines).

• Exposure to customer 360 / omnichannel data architectures.

• Familiarity with Portuguese or EU banking regulatory environments.

Profile

• A technical leader who has not lost touch with the platform, you can still read code, debug a pipeline and run a design review yourself.

• Decisive under ambiguity. Multiple parallel programmes; you make the call without escalating every issue.

• Comfortable challenging architects and external consultants on technical decisions, with evidence and without ego.

• Cost-aware. You think about the Azure invoice before you ship the design.

• Calm communicator who can de-escalate, align and bring people forward.