Data Scientist (Risk & Compliance) vs Analytics Engineer (dbt / SQL): Salary & Career Benchmarks in Portugal

In Portugal, Data Scientist (Risk & Compliance) roles typically command a higher median salary than Analytics Engineer (dbt / SQL) positions. According to our 2026 live benchmark data, a mid-level Data Scientist (Risk & Compliance) earns a median salary of €43K, whereas a Analytics Engineer (dbt / SQL) brings in roughly €35K (a gap of €8K at the median).

Seniority, tech stack, and location all move this gap. Senior practitioners in either discipline can exceed the upper range through specialist skills. See the skills premium section below for the specific certifications and tools that push offers to the top of the range.

While both positions are vital to a modern tech organisation, Data Scientist (Risk & Compliance) and Analytics Engineer (dbt / SQL) have fundamentally different daily workflows.

Data Scientist (Risk & Compliance) focuses primarily on building statistical and machine-learning models for credit risk, fraud detection, and regulatory compliance monitoring within a bank or fintech. Day-to-day work revolves around building and validating credit-risk or fraud-detection models, running model performance monitoring, documenting models for regulatory review, and working with compliance teams on model explainability requirements.

Analytics Engineer (dbt / SQL) focuses on transforming raw data into trusted, business-ready datasets using dbt modelling layers and semantic logic. Their time is spent writing and testing dbt models, maintaining data catalogues, defining shared metric logic with analysts, and enforcing data quality checks across the warehouse.

Transitioning between these two paths is achievable but requires targeted upskilling.

Moving from Data Scientist (Risk & Compliance) to Analytics Engineer (dbt / SQL): Data analysts with strong SQL and a working knowledge of dbt are the most natural fit, since the role sits at the intersection of engineering and analysis.

Moving from Analytics Engineer (dbt / SQL) to Data Scientist (Risk & Compliance):

Neither path requires starting from scratch. Professionals in both roles share underlying technology fluency; the gap is usually domain knowledge and specific tooling rather than core engineering fundamentals.

In Portugal in 2026, both roles are seeing demand, but with different drivers.

Data Scientist (Risk & Compliance) demand is very high, particularly in Portuguese banks and fintechs in Lisbon building risk and fraud models under Banco de Portugal supervisory expectations, led by employers such as Novo Banco and Feedzai. Analytics Engineer (dbt / SQL) demand is very high, concentrated in Data platform teams inside Lisbon nearshore delivery centres and fintechs, led by employers such as Farfetch and Critical Techworks.

Workspace flexibility significantly impacts total compensation value in Portugal.

Data Scientist (Risk & Compliance) roles score 45% on our remote-friendliness index (Moderate). This is because model development work can largely be done remotely, and Lisbon's fintech scale-ups have normalised distributed model development teams. Where in-office attendance is required, it is typically driven by model validation sign-off and regulator-facing documentation keep this role largely on-site at Banco de Portugal-regulated institutions in Lisbon.

Analytics Engineer (dbt / SQL) roles score 68% (High). Model-building and data-pipeline work is largely asynchronous and tool-driven, and Portuguese employers, competing against remote-first nearshore hiring, have generally kept flexible remote and hybrid arrangements is the primary driver of flexibility. When office days are required, it is usually for cross-functional data modelling discussions and stakeholder alignment sessions, with Lisbon-based employers increasingly formalising this into a two- or three-day hybrid schedule.