Senior Data Engineer
Satispay2 days ago
Location
Milan, Italy
Type
Full Time
Salary
EUR 51,000 – 66,500
Level
Senior
Role
Data Engineer
Posted
Jul 10, 2026
Full TimeSenior
The role
Summary
As a Senior Data Engineer at Satispay, you will architect and evolve a next-generation data lakehouse platform while empowering Data Analysts and business teams to autonomously model and analyze financial data. This role combines strategic platform ownership with hands-on technical leadership, requiring expertise in distributed systems, real-time streaming, and modern data stack technologies including Amazon Redshift, Apache Airflow, and dbt frameworks. You will drive innovation in machine learning infrastructure, data governance, and AI-assisted engineering while mentoring junior engineers in a fast-paced fintech environment.
What you'll do
Data Lakehouse Architecture & Redshift Platform Ownership: Lead the design, implementation, and evolution of Satispay's data lakehouse strategy, ensuring seamless integration with Amazon Redshift and Redshift Serverless for high-performance analytics at scale. Architect cost-efficient approaches to handle the data demands of a growing 6-million-user fintech platform while maintaining query performance and data integrity across all analytics workloads.
Analytics Engineering & dbt Framework Leadership: Establish and maintain the core dbt framework that empowers Data Analysts to independently contribute to data modeling. Implement CI/CD pipelines, comprehensive testing frameworks, and documentation standards that make analytics engineering decentralized, scalable, and maintainable. Champion best practices that enable self-service analytics across the organization.
Orchestration & Workflow Automation with Apache Airflow: Build, scale, and maintain reliable orchestration layers using Apache Airflow, designing and optimizing complex directed acyclic graphs (DAGs) that efficiently handle both batch and near-real-time workloads. Ensure robust monitoring, alerting, and recovery mechanisms that meet critical service level agreements for data delivery.
Machine Learning Platform & Feature Store Management: Own, architect, and scale Satispay's machine learning platform infrastructure, including the Feature Store that serves model training and real-time inference pipelines. Build robust data pipelines that provision collaborative analytics environments for Data Scientists and Analysts, enabling rapid experimentation and model deployment in production.
Real-Time Streaming & Transformation Pipelines: Design and operate streaming transformation pipelines using Apache Flink or Spark Streaming that power near-real-time analytics and feed the feature store. Move the platform beyond batch processing to support real-time financial data insights, event-driven architectures, and immediate decision-making capabilities.
AI-Assisted Development & Agentic Engineering Integration: Drive team-wide productivity improvements by evaluating, integrating, and maintaining AI-assisted development workflows. Leverage tools like Claude Code and deploy AI agents to automate routine data engineering tasks, enhance pipeline monitoring, and accelerate delivery cycles while maintaining code quality and governance standards.
Data Ingestion & Integration Management: Supervise managed ingestion workflows using Fivetran and maintain custom Python pipelines that ensure cost-efficient, resilient, and reliable data flow across the platform. Design robust error handling and retry mechanisms that guarantee data completeness and timeliness for downstream consumers.
Performance Optimization & Cost Management: Design and optimize the entire data platform for performance and cost efficiency across ingestion streams, transformations, feature store operations, and Redshift Serverless. Monitor and continuously improve query performance, storage utilization, and compute costs while maintaining service level objectives.
Data Governance, Security & Financial Compliance: Design and implement robust data governance frameworks, access control mechanisms, and privacy measures across all data assets. Ensure strict compliance with financial regulations (PSD2, GDPR, and other relevant standards) while maintaining data security and building trust with regulatory stakeholders.
Technical Mentorship & Engineering Standards Leadership: Act as a technical mentor for junior and mid-level data engineers, fostering their growth through code reviews, architectural discussions, and knowledge sharing. Champion documentation practices, establish engineering standards, and create processes that elevate the capabilities of the entire data engineering team.
What we look for
Technical
Advanced SQL & Data ManipulationExpert-level proficiency in SQL for complex data manipulation, analysis, and query optimization. Demonstrated ability to write performant SQL across analytical databases, including window functions, optimization techniques, and query execution plan analysis.
Python for Data EngineeringStrong hands-on experience building production-grade data pipelines, data processing applications, and infrastructure automation using Python. Proficiency with libraries like Pandas, PySpark, and custom API integration frameworks.
Apache Airflow OrchestrationProven expertise designing, building, and maintaining complex Apache Airflow DAGs in production environments. Experience with dynamic DAG generation, monitoring, alerting, and scaling Airflow clusters to handle high-volume workloads.
dbt Analytics Engineering FrameworkDeep knowledge of dbt project structure, macros, testing frameworks, and CI/CD integration. Ability to establish dbt best practices, code organization patterns, and documentation standards that enable team scalability.
Amazon Redshift & Data WarehousingHands-on experience with Amazon Redshift architecture, query optimization, and Redshift Serverless deployments. Understanding of distribution keys, sort keys, compression, vacuum operations, and cost optimization strategies specific to Redshift environments.
Real-Time Streaming TechnologiesProduction experience with Apache Flink, Spark Streaming, or equivalent streaming frameworks. Understanding of event processing, stateful computations, windowing, and building low-latency data pipelines for real-time analytics.
Feature Store ArchitectureExperience designing, implementing, or operating feature stores that serve machine learning models. Understanding of feature management, versioning, offline-to-online consistency, and integration with ML training and inference pipelines.
Data Quality & ObservabilityExpertise implementing data quality frameworks, data lineage tracking, and comprehensive monitoring solutions. Experience with tools like dbt testing, Great Expectations, and custom observability platforms to ensure data reliability.
Cloud Data Platform ArchitectureComprehensive understanding of modern cloud data stack architectures, including ETL/ELT patterns, lakehouse designs, data mesh principles, and self-service analytics platforms. Experience migrating or building platforms in AWS environments.
Data Security & Compliance EngineeringKnowledge of implementing data governance, access control mechanisms, encryption strategies, and compliance frameworks. Experience with PSD2, GDPR, and other financial regulations in regulated environments.
Education
Computer Science or Engineering DegreeBachelor's degree in Computer Science, Software Engineering, Data Engineering, or related field. Advanced degree (Master's) is valued but not required if compensated by exceptional industry experience.
Continuous Learning & CertificationsDemonstrated commitment to continuous learning through relevant certifications, courses, or self-directed study. AWS certifications (Solutions Architect, Data Engineer), dbt certification, or Apache Airflow expertise are valued indicators of commitment to technical excellence.
Experience
Enterprise Data Platform Design & ScalingMinimum 5+ years of hands-on experience designing, building, and scaling complex enterprise data platform architectures. Demonstrated success leading platform evolution from centralized to distributed architectures serving dozens to hundreds of analytics users.
Production Data Engineering at ScaleProven track record building and maintaining mission-critical data pipelines and platforms in production environments. Experience managing platforms that process billions of records, serve hundreds of daily queries, and maintain strict SLAs.
Leadership & MentorshipExperience mentoring junior and mid-level engineers, establishing engineering standards, and driving technical decisions that impact team capability and platform quality. Demonstrated ability to balance hands-on contribution with team leadership.
Cross-Functional CollaborationProven ability working closely with Data Analysts, Data Scientists, business stakeholders, and backend engineers. Experience translating business requirements into technical architecture and communicating complex technical concepts to non-technical audiences.
FinTech or Regulated Industry ExperiencePreferred experience in fintech, payments, or other highly regulated industries. Understanding of financial compliance requirements, transaction processing, and the operational demands of financial services platforms.
Skills
Required skills
SQLExpert-level SQL proficiency for complex analytical queries, optimization, and data modeling
PythonProduction-grade Python programming for building scalable data pipelines and automation
Apache AirflowDemonstrated expertise building, scaling, and maintaining Airflow DAGs in production environments
dbtStrong hands-on experience with dbt project architecture, testing, and CI/CD integration
Amazon RedshiftProduction experience with Redshift architecture, optimization, and Redshift Serverless deployments
Data Architecture & DesignComprehensive understanding of batch and real-time data architectures, data modeling, and platform design patterns
Data Quality & GovernanceExperience implementing data quality frameworks, monitoring, and governance controls
Cloud Engineering (AWS)Hands-on AWS experience with data services, infrastructure, and cloud architecture patterns
Italian & English FluencyFluent in both Italian and English for seamless communication with international teams and stakeholders
Nice to have
Apache Flink or Spark StreamingProduction experience building real-time streaming pipelines and event processing systems
Java or ScalaExperience with Java or Scala for building robust data pipeline components and backend services
Feature Store ImplementationHands-on experience designing or operating feature stores for machine learning platforms
Data Mesh ArchitectureUnderstanding of data mesh principles, federated data ownership, and decentralized data platform design
Fivetran or Managed Ingestion ToolsExperience configuring and managing Fivetran connectors or similar managed ingestion solutions
Machine Learning Platform EngineeringExperience building infrastructure and pipelines that support ML model development, training, and deployment
AI-Assisted Development ToolsFamiliarity with Claude Code, GitHub Copilot, or other AI coding assistants for development acceleration
FinTech Domain KnowledgeExperience in payments, banking, or financial technology platforms and their operational requirements
Kubernetes & Container OrchestrationExperience deploying and scaling data workloads using containerization and orchestration platforms
Great Expectations or dbt TestingAdvanced data quality testing and validation framework expertise
Compensation & benefits
Salary
EUR 51,000 – 66,500 (annual)
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Satispay is a European fintech company that provides mobile payment solutions and financial services to consumers and businesses. The company operates a digital payment platform that enables peer-to-peer transfers, merchant payments, and business transactions through a mobile app. Satispay focuses on simplifying payments in the European market, particularly in Italy, by offering a cost-effective alternative to traditional payment methods. The company serves a growing base of users and merchants across multiple European countries, operating in the digital payments and financial technology sector.
Milan, ItalyFounded 2013satispay.com/en-it/work-at-satispay
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