Senior Data Engineer

About the role

You will architect and evolve Satispay's next-generation data platform, defining the long-term strategy for our Data Lakehouse and ensuring it delivers high-performance analytics for thousands of business decisions every day. In this role, you own the full lifecycle of critical data infrastructure, from initial design and implementation through to scaling, governance, and continuous optimization in production. You will enable autonomy across Data Analysts and business teams by establishing robust frameworks, clear best practices, and reliable tooling that remove friction and unlock faster insights. Day by day, you will balance innovation with reliability, ensuring new capabilities are delivered securely, scalably, and with clear ownership. You will act as a technical leader and mentor, elevating the engineering culture through documentation, standards, and hands-on collaboration. Your work will directly influence how quickly and safely the company can experiment, report, and make data-driven decisions. You will partner closely with Data Scientists, Analysts, and Product teams to turn business questions into resilient data products.

Key facts

What you'll do

• 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 by owning the core dbt framework, establishing best practices, CI/CD pipelines, and robust testing frameworks to make analytics engineering scalable and decentralised.
• 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 and building robust data pipelines for model training and inference.
• 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, moving the platform beyond batch.
• AI Tooling & Agentic Engineering
• Drive team-wide productivity gains by exploring, integrating, and maintaining AI-assisted development workflows, including tools like Claude Code and deploying AI agents to automate tasks and optimise pipeline monitoring.
• 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, including ingestion streams, transformations, feature store, and Redshift Serverless, while 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 while maintaining trust.
• Mentorship & Tech Leadership
• Act as a technical mentor for junior and mid-level engineers, champion documentation, and establish engineering standards that elevate the entire team's capabilities.

Requirements

• You have a 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.
• You are highly skilled in SQL for data manipulation and analysis and have practical experience with at least one of the following: Python, Java, or Scala for building robust data pipelines.
• You are familiar with both batch and real-time streaming data architectures and understand the principles behind designing scalable and resilient data systems.
• You have a strong passion for deeply understanding data, its meaning, the critical importance of preparing it correctly, and the methodologies for ensuring its quality and unwavering consistency.
• You understand how to transition from centralised data delivery to a platform model, designing tools and guardrails that allow Data Analysts to safely self-serve and own their data models.
• You are excited about the intersection of data engineering and AI, with an interest in LLMs, and integrating AI coding assistants (like Claude Code) into the development lifecycle.
• You communicate clearly and persuasively, adapting your approach to build trust and engage effectively with diverse stakeholders across technical and business teams.
• You are fluent in both Italian and English, enabling seamless communication within our international team and with our customers.

Nice to have

• Experience with dbt Cloud and Dataform.
• Experience with data visualization tools such as Tableau or Looker.
• Experience with financial services or payments domain.
• Experience with infrastructure as code and cloud platforms, such as AWS.

Practical notes

This is a full-time, onsite role based in Milan. The position requires adherence to standard working hours as defined by company policy and local regulations. Applicants must be eligible to work in Italy without sponsorship. The recruitment process will only contact shortlisted candidates.