FinCrime Analytics Engineer

Satispay; Barcelona; Presencial; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Stock options

Meal vouchers

Relocation support

Professional development

Unlimited PTO

Hybrid work policy

Parental leave

Descripción de la vacante

Satispay is hiring a FinCrime Analytics Engineer in Barcelona to lead our data strategy, ensuring analytical data is readily available, well-structured, and aligned with operational needs.

You will design data models, build pipelines, and create AI-powered workflows that accelerate analytics and enable self-service for key stakeholders. Strong SQL/Python skills and 5+ years in data engineering are required.

Formación

• 5+ years in data engineering or analytics engineering.
• Proficient in SQL and Python; experience with Big Data and ETL pipelines.
• Experience with dbt, Airflow, Spark or similar tech.
• Excellent communication skills; fluent in English.
• Nice to have: experience with Feature Stores, Graph Databases, ML Engineering.

Responsabilidades

• Design data architecture and pipelines aligned with federated data strategy.
• Ensure high-quality data collection and manage high-volume batch processing.
• Define AI-powered workflows for data transformation and exploration.
• Direct cross-functional initiatives and translate insights into actions.
• Develop feature store capabilities for scalable feature usage.
• Simplify complex data models to improve query performance.

Conocimientos

SQL

Python

Big Data

ETL pipelines

dbt

Airflow

Spark

English

Communication

Herramientas

dbt

Airflow

Spark

Descripción del empleo

About us

Traditional banking has never really given you control over your financial life. Satispay exists to change that: to empower people through finance.

That means making financial services easy and accessible for over 6.5M users. We started with payments, then benefits, investing, cards... and we’re not done. Not even close. We follow the same logic every time: find a real problem, solve it properly, then look for the next one. The destination? To build the most loved financial platform in the world. If you own outcomes rather than tasks, stay close to what users need, and refuse to wait for someone else to fix what's broken — you'll find people here who work exactly in the same way. And together, you'll build something worth being proud of.

What you'll be doing

As our FinCrime Analytics Engineer, you'll drive our data strategy to elevate risk decision-making by ensuring all analytical data is readily available, well-structured, and fully aligned with our operational needs.

Here’s what that looks like in practice:

• Design Data Architecture - Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy, ensuring scalable and governed data ownership.

• Data Integrity and Processing - Ensure the collection of high-quality data and manage high-volume data batch processing to maintain optimal performance for dashboards and analytical models.

• Define AI Agentic Workflows - Design and implement AI-powered agentic workflows for data transformation and exploration, accelerating analytical capabilities and enabling self-service for key stakeholders.

• Stakeholder Management & Communication - Independently direct cross-functional initiatives across diverse business requirements, turning technical insights into impactful actions and data model optimizations.

• Build Feature Store Capabilities - Develop high-value features to populate the feature store using optimized code capable of processing and executing across high volumes of data.

• Challenge and Simplify - Simplify complex data models into clear, efficient data relations that can be easily queried with SQL to improve overall performance and ensure high data quality.

Who we’re looking for

This role needs someone proactive, curious, and eager to take full ownership of our data strategy to elevate risk decision-making.

• Experience – 5+ years in data engineering or analytics engineering.

• Technical Proficiency – High proficiency in SQL, Python, Big Data, distributed processing, dbt, Airflow, Spark, or similar technologies, with hands‑on experience building ETL data pipelines.

• Communication – Excellent communication skills and fluency in English.

• Nice to Have – Experience with Feature Stores, Graph Databases, and Machine Learning Engineering.

Don’t worry if you don’t tick every box. We believe in the power of different viewpoints and strengths. Your unique perspective is important as we build something special: if you’re passionate and can make a difference, we truly encourage you to apply.

CareAbout: how we support your impact

We move fast, and evolution never stops. It’s a fun ride, but it can be challenging. To make sure our people truly thrive, we’re committed to making their lives easier, both in the office and out in the world. That’s why we created CareAbout:

• Health: private insurance for you and your family, psychological support with Serenis, mental health workshops.

• Financial resources: Stock Option Plan, meal vouchers, relocation support if you’re moving countries.

• Growth and development: professional development programs, internal mobility, language courses with Preply.

• Flexibility: unlimited PTO, hybrid working policy*, flexible working hours.

• Family: enhanced parental leave, additional leave for child sickness.

*We embrace three days per week in-office (Tuesday and Thursday + 1 of your choice), with the option to request extra remote time.

Equal opportunity employer

At Satispay, we’re proud to be an equal opportunity employer. We celebrate diversity and inclusion, welcoming individuals of all backgrounds. This opportunity is open to everyone, regardless - for instance - of race, colour, religion, sex, gender identity, sexual orientation, and national origin.

Join us in a workplace where everyone belongs!

Learn more about us

Curious what it's actually like here? Our values and pillars shape how we work every day: explore them here.

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