Cloud Data Engineer | Digital Pills

• Way of working: hybrid, office in Turin (city centre), around 8 days per month on site, managed flexibly

• Key tech skills: Python, advanced SQL, ETL/ELT pipelines, solution design, GCP, Azure or AWS, IAM and networking, Cloud Run/Functions, data warehouses, AI tools for development

• Experience: at least 3 years as a software engineer or data engineer, with solid hands-on experience

• Gross annual salary: €32,000 - €42,000 + annual bonus + welfare

About the company

Welyk is recruiting on behalf of Digital Pills, a consulting company focused exclusively on data, based in Turin with around 30 people. The company covers the entire data value chain: data strategy, data engineering, analytics engineering, BI and data science, and over the last two years it has significantly strengthened its AI practice. It works with large international clients (including HelloFresh, Airalo and Last Minute) and Italian enterprise brands, and is pursuing an international expansion. It also dedicates a significant part of its activity to the non-profit sector, including pro bono projects for organisations such as AIRC and Save the Children.

Digital Pills recently received an investment from RIF-T, a vehicle controlled by Equiter and funded by Fondazione Compagnia di San Paolo, to support its scale-up phase and its evolution towards a model based on proprietary accelerators and products. The person will join the delivery team, where projects are organised in small, dynamic teams: on small and medium projects they work autonomously as the technical lead, on larger projects within structured teams, together with the account who manages the client relationship. It is a role where data engineering, cloud engineering and software engineering intersect, in heterogeneous and constantly evolving technical environments.

What you'll do

• Be the technical lead on small and medium projects, following them autonomously from solution design to production release

• On larger, cross-cutting projects, work in structured project teams, supported by senior colleagues to ensure alignment with the overall architecture and company best practices, together with the account who manages the client relationship

• Design and build cloud-native data pipelines and platforms on GCP, Azure and AWS, with a focus on robust ETL/ELT and efficient data integrations

• Design and manage cloud infrastructure: networking, IAM, services, monitoring

• Develop connectors and lightweight backend services in Python

• Work on advanced projects: integrations between complex systems, data replication and synchronization, productized ETL platforms and AI-based services, such as RAG systems, Copilot-style architectures, MCP servers and LLM API integrations

Requirements

• At least 3 years of experience as a software engineer or data engineer: this is not a junior position, we need someone already able to work autonomously

• Solid software engineering foundations and the ability to design the solution, not only implement it

• Experience with projects followed end-to-end, from design to release

• Advanced SQL and data modelling, experience building and running ETL/ELT pipelines, good knowledge of data warehouses and transactional databases

• Solid Python for data pipelines, connectors and lightweight backend services, Git, code review and collaborative development, clean, testable and maintainable code

• Hands-on experience with at least one cloud provider (GCP, Azure or AWS, no preference): IAM and service accounts, networking and VPC concepts, Cloud Run, Functions and VMs, monitoring and logging

• Use of AI tools (Claude Code, Cursor, GitHub Copilot or similar) for implementation, design or analysis tasks

• Master's degree in Computer Engineering, Computer Science or equivalent practical experience

• Fluent Italian and professional working English

Nice to have

• Experience designing and integrating AI services via API (OpenAI, Anthropic, Azure OpenAI), including RAG systems, Copilot-style architectures and MCP servers, handling authentication, rate limits, latency and error handling

• MLOps: deploying machine learning models in the cloud and integrating data pipelines with models

• Analytics engineering: experience with data from marketing and advertising platforms (Google Analytics, Google Ads, Meta Ads or similar), from raw data transformation to models for analytics and attribution

• Experience in startups or small tech companies

You're the right person if

You have solid IT foundations and you