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Senior Data Engineer

Milan, Italy · Milan, Lombardia, Italy

Pay
Up to €88,000/year · Gross — pay source
*We embrace two days per week in-office (Tuesday and Thursday), with the option to request extra remote time. Salary: up to €88,000 gross per annum. This range is set using objective, gender-neutral criteria for the role's core requirements. However, we do not believe in putting a ceiling on talent. The final compensation package is tailored according to your unique experience and expertise. If your skills go beyond the standard profile, apply anyway so we can discuss a package that reflects your true value.
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Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Tech & Product › Engineering — team source
Department: Tech & Product › Engineering
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status?
From the employer’s application form

What you’ll work on

Full posting
  • Lead the design of the modern Data Lakehouse on Amazon Redshift

  • Own the dbt framework and CI/CD and testing practices for analysts

  • Build and scale Apache Airflow orchestration for batch and near-real-time work

  • Own the ML platform, Feature Store and model training pipelines

  • Design streaming pipelines with Apache Flink or Spark Streaming

From the employer’s posting
Lead the design and implementation of our modern Data Lakehouse strategy, ensuring seamless integration with Amazon Redshift & Redshift Serverless
owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks
Build, scale, and maintain reliable orchestration layers using Apache Airflow, optimising complex DAGs for both batch and near-real-time workloads
Own, architect, and scale Satispay’s Machine Learning Platform, managing our Feature Store, building robust data pipelines for model training/inference
Design and operate streaming transformation pipelines (e.g. Apache Flink, Spark Streaming)

Tools in this posting

  • Java
  • Python
  • Scala
  • SQL
  • dbt
  • Fivetran
  • Redshift
  • Spark
  • Airflow
Source — Tool mentions in context
- Relevant education and technical background - Degree in Computer Science, Engineering, or a related field, backed by 5+ years of hands-on experience designing, scaling, and maintaining complex enterprise data platform architectures. - Programming Expertise - Highly skilled in SQL for data manipulation and analysis, with practical experience in Python, Java, or Scala for building robust data pipelines. - Architectural Knowledge - Familiarity with both batch and real-time streaming data architectures and principles for designing scalable and resilient systems.
- AI Tooling & Agentic Engineering - Drive team-wide productivity gains by exploring, integrating, and maintaining AI-assisted development workflows (e.g., leveraging tools like Claude Code and deploying AI agents). - Ingestion & Integration - Supervise managed ingestion workflows (Fivetran) and custom Python pipelines, ensuring cost-efficient, resilient, and reliable data flow across systems. - Performance, Cost & Reliability - Design for performance and cost across the entire platform, owning data quality, observability, and the SLAs your consumers depend on.
- Data Platform Architecture & Evolution - Lead the design and implementation of our modern Data Lakehouse strategy, ensuring seamless integration with Amazon Redshift & Redshift Serverless for high-performance analytics. - Self-Service Enablement & Analytics Engineering - Empower Data Analysts to contribute directly to data modelling, owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks. - Orchestration & Workflow Automation - Build, scale, and maintain reliable orchestration layers using Apache Airflow, optimising complex DAGs for both batch and near-real-time workloads.
Here's what that looks like in practice: - Data Platform Architecture & Evolution - Lead the design and implementation of our modern Data Lakehouse strategy, ensuring seamless integration with Amazon Redshift & Redshift Serverless for high-performance analytics. - Self-Service Enablement & Analytics Engineering - Empower Data Analysts to contribute directly to data modelling, owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks.
- ML Platform Ownership & Feature Store Management - Own, architect, and scale Satispay’s Machine Learning Platform, managing our Feature Store, building robust data pipelines for model training/inference, and provisioning collaborative analytics environments. - Streaming & Real-Time Data - Design and operate streaming transformation pipelines (e.g. Apache Flink, Spark Streaming) that power near-real-time analytics and feed the feature store. - AI Tooling & Agentic Engineering - Drive team-wide productivity gains by exploring, integrating, and maintaining AI-assisted development workflows (e.g., leveraging tools like Claude Code and deploying AI agents).
- Self-Service Enablement & Analytics Engineering - Empower Data Analysts to contribute directly to data modelling, owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks. - Orchestration & Workflow Automation - Build, scale, and maintain reliable orchestration layers using Apache Airflow, optimising complex DAGs for both batch and near-real-time workloads. - ML Platform Ownership & Feature Store Management - Own, architect, and scale Satispay’s Machine Learning Platform, managing our Feature Store, building robust data pipelines for model training/inference, and provisioning collaborative analytics environments.

About Satispay

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.

In the employer’s words · Read in context · Company website ↗

Posting record

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Open 3 monthsWe first saw this posting 109 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

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Live
First seen by us
Jul 13, 2026 · 109 days ago
Recorded sightings
145
Last seen by us
Oct 30, 2026
Employer says posted
Jul 10, 2026

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Job description

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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 Senior Data Engineer, you will shape the evolution of our next-generation data platform, architecting, scaling, and governing an ecosystem that empowers Data Analysts and business teams to autonomously model, analyse, and leverage data safely.

Here's what that looks like in practice:

  • Data Platform Architecture & Evolution - Lead the design and implementation of our modern Data Lakehouse strategy, ensuring seamless integration with Amazon Redshift & Redshift Serverless for high-performance analytics.

  • Self-Service Enablement & Analytics Engineering - Empower Data Analysts to contribute directly to data modelling, owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks.

  • Orchestration & Workflow Automation - Build, scale, and maintain reliable orchestration layers using Apache Airflow, optimising complex DAGs for both batch and near-real-time workloads.

  • ML Platform Ownership & Feature Store Management - Own, architect, and scale Satispay’s Machine Learning Platform, managing our Feature Store, building robust data pipelines for model training/inference, and provisioning collaborative analytics environments.

  • Streaming & Real-Time Data - Design and operate streaming transformation pipelines (e.g. Apache Flink, Spark Streaming) that power near-real-time analytics and feed the feature store.

  • AI Tooling & Agentic Engineering - Drive team-wide productivity gains by exploring, integrating, and maintaining AI-assisted development workflows (e.g., leveraging tools like Claude Code and deploying AI agents).

  • Ingestion & Integration - Supervise managed ingestion workflows (Fivetran) and custom Python pipelines, ensuring cost-efficient, resilient, and reliable data flow across systems.

  • Performance, Cost & Reliability - Design for performance and cost across the entire platform, owning data quality, observability, and the SLAs your consumers depend on.

  • Data Governance, Security & Compliance - Design robust data security, access control, and privacy measures across all data assets to ensure strict compliance with financial regulations.

  • Mentorship & Tech Leadership - Act as a technical mentor for junior/mid-level engineers, champion documentation, and establish engineering standards that elevate team capabilities.

Who we're looking for

This role needs someone who is a problem-solver, loves teamwork, and gets things done with high curiosity and readiness for real ownership.

  • Relevant education and technical background - Degree in Computer Science, Engineering, or a related field, backed by 5+ years of hands-on experience designing, scaling, and maintaining complex enterprise data platform architectures.

  • Programming Expertise - Highly skilled in SQL for data manipulation and analysis, with practical experience in Python, Java, or Scala for building robust data pipelines.

  • Architectural Knowledge - Familiarity with both batch and real-time streaming data architectures and principles for designing scalable and resilient systems.

  • Data-Oriented Mindset - Strong passion for deeply understanding data, its meaning, the importance of correct preparation, and methodologies for quality and consistency.

  • Platform & Mesh Mindset - Understanding of how to transition from centralised data delivery to a platform model with guardrails for self-service analytics.

  • Forward-Thinking & AI Curious - Excited about the intersection of data engineering and AI, with interest in LLMs and integrating AI coding assistants into development.

  • Structured communication and stakeholder management - Clear and persuasive communication skills, adapting your approach to build trust across technical and business teams.

  • Language proficiency - Fluent in both Italian and English for seamless communication across an international team.

  • Passion for FinTech or Startup environments - Genuine passion for fast-paced FinTech/startup ecosystems.

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.

*We embrace two days per week in-office (Tuesday and Thursday), with the option to request extra remote time.

Salary: up to €88,000 gross per annum.

This range is set using objective, gender-neutral criteria for the role's core requirements. However, we do not believe in putting a ceiling on talent. The final compensation package is tailored according to your unique experience and expertise. If your skills go beyond the standard profile, apply anyway so we can discuss a package that reflects your true value.

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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Pay
*We embrace two days per week in-office (Tuesday and Thursday), with the option to request extra remote time. Salary: up to €88,000 gross per annum. This range is set using objective, gender-neutral criteria for the role's core requirements. However, we do not believe in putting a ceiling on talent. The final compensation package is tailored according to your unique experience and expertise. If your skills go beyond the standard profile, apply anyway so we can discuss a package that reflects your true value.
Location & working pattern

Milan, Lombardia, Italy

- ⚙️ Growth and development: professional development programs, internal mobility, language courses with Preply. - 🌱 Flexibility: unlimited PTO, hybrid working policy*, flexible working hours. *We embrace two days per week in-office (Tuesday and Thursday), with the option to request extra remote time. Salary: up to €88,000 gross per annum.
More source context
Curious what it's actually like here? Our values and pillars shape how we work every day: explore them here. #LI-HYBRID #LI-VR1
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We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting